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. 2021 Sep 30;43:41. doi: 10.1186/s41021-021-00206-1

Bacterial mutagenicity test data: collection by the task force of the Japan pharmaceutical manufacturers association

Atsushi Hakura 1,✉, Takumi Awogi 2, Toshiyuki Shiragiku 3, Atsushi Ohigashi 4, Mika Yamamoto 5, Kayoko Kanasaki 6, Hiroaki Oka 7, Yasuaki Dewa 8, Shunsuke Ozawa 8, Kouji Sakamoto 9, Tatsuya Kato 10, Eiji Yamamura 10
PMCID: PMC8482598  PMID: 34593056

Abstract

Background

Ames test is used worldwide for detecting the bacterial mutagenicity of chemicals. In silico analyses of bacterial mutagenicity have recently gained acceptance by regulatory agencies; however, current in silico models for prediction remain to be improved. The Japan Pharmaceutical Manufacturers Association (JPMA) organized a task force in 2017 in which eight Japanese pharmaceutical companies had participated. The purpose of this task force was to disclose a piece of pharmaceutical companies’ proprietary Ames test data.

Results

Ames test data for 99 chemicals of various chemical classes were collected for disclosure in this study. These chemicals are related to the manufacturing process of pharmaceutical drugs, including reagents, synthetic intermediates, and drug substances. The structure-activity (mutagenicity) relationships are discussed in relation to structural alerts for each chemical class. In addition, in silico analyses of these chemicals were conducted using a knowledge-based model of Derek Nexus (Derek) and a statistics-based model (GT1_BMUT module) of CASE Ultra. To calculate the effectiveness of these models, 89 chemicals for Derek and 54 chemicals for CASE Ultra were selected; major exclusions were the salt form of four chemicals that were tested both in the salt and free forms for both models, and 35 chemicals called “known” positives or negatives for CASE Ultra. For Derek, the sensitivity, specificity, and accuracy were 65% (15/23), 71% (47/66), and 70% (62/89), respectively. The sensitivity, specificity, and accuracy were 50% (6/12), 60% (25/42), and 57% (31/54) for CASE Ultra, respectively. The ratio of overall disagreement between the CASE Ultra “known” positives/negatives and the actual test results was 11% (4/35). In this study, 19 out of 28 mutagens (68%) were detected with TA100 and/or TA98, and 9 out of 28 mutagens (32%) were detected with either TA1535, TA1537, WP2uvrA, or their combination.

Conclusion

The Ames test data presented here will help avoid duplicated Ames testing in some cases, support duplicate testing in other cases, improve in silico models, and enhance our understanding of the mechanisms of mutagenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41021-021-00206-1.

Keywords: Ames test, Mutagenicity, Bacteria, In silico, Structure-activity relationship, Derek Nexus, CASE Ultra

Introduction

The bacterial mutagenicity test, known as Ames test, is used worldwide to detect the mutagenicity of chemicals [1, 2]. Ames test is utilized not only for research purposes but also for submission to regulatory agencies for the approval of chemical substances [3, 4]. Recently, in silico evaluation of bacterial mutagenicity has been accepted by regulatory agencies [e.g., the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) M7 guideline [5] for hazard identification of mutagenic impurities in medicinal drugs]. In recent years, several in silico models for predicting bacterial mutagenicity have been developed. However, the prediction level is not fully satisfactory and remains to be improved [6–8]. One way to improve this is to collect Ames test data, particularly for chemicals in some chemical classes where a limited number of test data are available.

For this reason, the Japan Pharmaceutical Manufacturers Association (JPMA) organized a task force for Ames data sharing. The purpose of this task force was to disclose a piece of pharmaceutical companies’ proprietary Ames test data to make them available to anyone for utilization in research or submission to regulatory agencies, and to improve in silico models by using them as training set examples. Eight Japanese pharmaceutical companies participated in this task force, and Ames test data for 99 chemicals were collected. These chemicals are related to the manufacturing process of pharmaceutical drugs, including reagents, synthetic intermediates, and drug substances. In addition, in silico analyses of these chemicals for bacterial mutagenicity were conducted using a knowledge-based model (Derek Nexus, Lhasa Limited) or a statistics-based model (CASE Ultra, MultiCASE Inc.).

In this report, we present the Ames test data and in silico predictions for 99 chemicals of various chemical classes and discuss their structure-activity relationships in relation to structural alerts for each chemical class.

Materials and methods

Materials

Ninety-nine chemicals were tested and collected by this task force. Table 1 lists the chemical identification (ID), chemical name, CAS registry number (CAS No.), source, purity of the test chemicals used, and test site. Table 2 lists the chemical ID, chemical name (arranged by chemical classes), chemical structure, solvent used to dissolve the test chemicals, summarized Ames test results, and in silico analyses. In this study, free and salt forms were treated as different chemicals.

Table 1.

Chemical ID, test chemical, CAS No. source or supplier of test chemical, purity, and test site

Chemical ID Test chemical CAS No. Source or supplier of test chemical Purity (%) Test site
1 1-Iodo-4-nitrobenzene 636–98-6 Maruzen Chemicals 99.9 CERI
2 2-Nitro-5-(1-piperazinyl)benzaldehyde HCl 13236300a Otsuka Pharmaceutical 100 JISHA
3 Methyl 2-methyl-3-nitrobenzoate 59382–59-1 Otsuka Pharmaceutical 99.57 JISHA
4 2-Nitro-5-(1-piperazinyl)benzaldehyde dimethyl acetal 101291629a Otsuka Pharmaceutical 99.8 JISHA
5 5-Chloro-2-nitrobenzaldehyde dimethyl acetal 13796–06-0 Otsuka Pharmaceutical 99.97 JISHA
6 2-Nitro-5-(1-piperazinyl)cinnamic acid NR Otsuka Pharmaceutical 99.8 JISHA
7 2-Fluoro-4-nitrophenol 403–19-0 Tokyo Chemical Industry 99.6 BoZo Research Center
8 3-Hydroxy-4-nitrobenzoic acid 619–14-7 Eisai 99.6 UBE
9 Pranidipine; Methyl (2E)-phenylprop-2-en-1-yl 2,6-dimethyl-4-(3-nitrophenyl)-1,4-dihydropyridine-3,5-dicarboxylate 99522–79-9 Otsuka Pharmaceutical 99.97 Otsuka Pharmaceutical
10 4-Amino-2-fluorophenol 399–96-2 Tokyo Chemical Industry 99.4 BoZo Research Center
11 Methyl 3-amino-2-methyl benzoate 18583–89-6 Otsuka Pharmaceutical 94.43 JISHA
12 Sodium 3-[2-amino-5-(1-piperazinyl)phenyl]propionate 101328646a Otsuka Pharmaceutical 99.5 JISHA
13 Methyl 4-amino-2-methoxybenzoate 27492–84-8 Tokyo Chemical Industry 98.9 BoZo Research Center
14 Methyl 3-amino-4,6-dibromo-2-methylbenzoate 119916–05-1 Otsuka Pharmaceutical 98.74 JISHA
15 4-(2-Methoxy-phenyl)-thiazol-2-ylamine 93209–95-1 Shionogi 99.99 CMIC Pharma Science
16 4-Hexyl-1,3-thiazol-2-amine 90770–58-4 Shionogi 99.72 CMIC Pharma Science
17 2-Amino-4-hydroxythiazole 7146–26-1 Oakwood Products 98 LSI Medience
18 Thiazole-2,4-diamine 67355–26-4 Oxchem 98 LSI Medience
19 6-(2,3-Epoxypropoxy)-2(1H)-quinolinone 143343–78-6 Otsuka Pharmaceutical 94.44 JISHA
20 6-(4-(3,4-Dimethoxybenzoyl)-2,3-dihydroxypiperazin-1-yl)-3,4-dihydriquinolin-2(1H)-one NR Otsuka Pharmaceutical 98.12 Otsuka Pharmaceutical
21 8-Hydroxy-2(1H)-quinolinone 15450–76-7 Otsuka Pharmaceutical 99.55 JISHA
22 3,4-Dimethoxy-N-{2-[(2-oxo-1,2,3,4-tetrahydroquinolin-6-yl)amino]ethyl}benzamide NR Otsuka Pharmaceutical 99.96 Otsuka Pharmaceutical
23 6-(3-Oxopiperazin-1-yl)-3,4-dihydroquinolin-2(1H)-one NR Otsuka Pharmaceutical 99.56 Otsuka Pharmaceutical
24 3,4-Dihydro-5-(1-piperazinyl)-2-(1H) quinolinone 87154–95-8 Otsuka Pharmaceutical > 99.9 JISHA
25 6-(4-(4-Hydroxy-3-methoxybenxoyl)piperazin-1-yl)-3,4-dihydroquinolin-2(1H)-one NR Otsuka Pharmaceutical 99.87 Otsuka Pharmaceutical
26 6-(1-Cyclohexyl-1H-tetrazol-5-yl)butoxy]-2(1H)-quinolinone 73963–62-9 Otsuka Pharmaceutical 100 Otsuka Pharmaceutical
27 trans-3,4-Dihydro-6-[4-[1-(4-hydroxycyclohexyl)-1H-tetrazol-5-yl]butoxy]-2(1H)-quinolinone 87153–04-6 Otsuka Pharmaceutical 99.93 Otsuka Pharmaceutical
28 Grepafloxacin; (RS)-1-Cyclopropyl-6-fluoro-5-methyl-7-(3-methylpiperazin-1-yl)-4-oxo-quinoline-3-carboxylic acid 119914–60-2 Otsuka Pharmaceutical 99.66 JISHA
29 Grepafloxacin HCl; (RS)-1-Cyclopropyl-6-fluoro-5-methyl-7-(3-methylpiperazin-1-yl)-4-oxo-quinoline-3-carboxylic acid monohydrochloride 161967–81–3 Otsuka Pharmaceutical 99.59 Otsuka Pharmaceutical
30 Ethyl 1-cyclopropyl-7-brorno-6-fluoro-1,4-dihydro-5-methyl-4-oxo-3-quinolinecarboxylate 119916–33-5 Otsuka Pharmaceutical 99.88 JISHA
31 2,4-Bis(trimethylsiloxy)-5-fluoropyrimidine 17242–85-2 Otsuka Pharmaceutical 99.3 JISHA
32 1,3-Dimethyl-2,4-pyrimidinedione 874–14-6 Otsuka Pharmaceutical 99.6 JISHA
33 1-(Ethoxymethyl)-5-fluoro-pyrimidine-2,4-dione 57610–22-7 Otsuka Pharmaceutical 99.7 JISHA
34 3-(1-Ethoxymethyl-5-fluoro-1,2,3,4-tetrahydro-2,4-dioxopyrimidin-3-yl)carbonylbenzoic acid 129971–17-1 Otsuka Pharmaceutical 99 JISHA
35 3-(3-Benzyloxycarbonylbenzoyl)-1-ethoxymethyl-5-fluoro-2,4-pyrimidinedione NR Otsuka Pharmaceutical 99.8 JISHA
36 1-Hydroxybenzotriazole hydrate 123333–53-9 Otsuka Chemical 99 BML
37 3H-[1,2,3]Triazolo[4,5-b]pyridin-3-ol 39968–33-7 Tokyo Chemical Industry 99 BML
38 1-[Bis (dimethylamino)methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium 3-oxid hexafluorophosphate 148893–10-1 Sigma-Aldrich 99 BML
39 Methylcarbamoyl-phenyloxadiazole 1374817–07-8 Shionogi 98.77 CERI
40 4-(4,6-Dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride n-hydrate 3945-69-5 Tokuyama 84.8 BML
41 N-Phenylbis(trifluoromethanesulfonimide) 37595–74-7 Tokyo Chemical Industry 99.9 SNBL
42 1,1,1-Trifluoro-N-phenylmethanesulfonamide 456–64-4 Tokyo Chemical Industry 99.9 SNBL
43 Perfluoro-1-butanesulfonyl fluoride 375–72-4 Funakoshi > 90 BML
44 Diisopropyl sulfate 2973-10-6 Tokyo Chemical Industry 97 BML
45 Methyl p-toluenesulfonate 80–48-8 Kanto Chemical 98 BML
46 Ethyl trifluoromethanesulfonate 425–75-2 Tokyo Chemical Industry 99.8 SNBL
47 2-Nitrobenzenesulfonyl chloride 1694-92-4 Mitsubishi Tanabe Pharma 100.1 Koei Techno
48 p-Toluenesulfonyl chloride 98–59-9 Tokyo Chemical Industry 99 BML
49 4,6-Dibromo-3-fluoro-2-methylbenzoyl chloride 11916–28-8 Otsuka Pharmaceutical 99.18 JISHA
50 Benzyl 3-chloroformylbenzoate 67852–96-4 Otsuka Pharmaceutical 99.3 JISHA
51 3-(1-Ethoxymethyl-5-fluoro-1,2,3,4-tetrahydro-2,4-dioxopyrimidin-3-yl)carbonylbenzoyl chloride 1380098–51-0 Otsuka Pharmaceutical 91.1 JISHA
52 6-(3-Chloro-2-hydroxypropoxy)-2(1H)-quinolinone 128669–85-8 Otsuka Pharmaceutical 95.18 JISHA
53 Chloroacetonitrile 107–14-2 Tokyo Chemical Industry 99.9 LSI Medience
54 1-Bromohexane 111–25-1 Tokyo Chemical Industry 99.8 BSRC
55 2-Chloro-N-methoxy-N-methylacetamide 67442–07-3 Tokyo Chemical Industry 99.9 CMIC Pharma Science
56 Ethyl 5-chloro-2-[2-(trifluoromethyl)phenyl]pentanimidate HCl 1123197–78-3 Eisai 97.8 UBE
57 Liothyronine sodium 55–06-1 Acros Organics 95 Taisho
58 (4-Bromo-3,5-dimethoxyphenyl)methanol 61367–62-2 Eisai 100 UBE
59 Ethyl (4,6-dibromo-3-fluoro-2-methylbenzoyl)acetate 119916–30-2 Otsuka Pharmaceutical 98.88 JISHA
60 Catena-m-[2-ethoxycarbonyl-3-(4,6-dibromo-3-fluoro-2-methylphenyl)-3-oxidoacrylato(2-)-O,O′,O″,O″′]magnesium (II) NR Otsuka Pharmaceutical 87.2 JISHA
61 Methyl 4,6-dibromo-3-fluoro-2-methylbenzoate 119916–08-4 Otsuka Pharmaceutical 99.72 JISHA
62 4,6-Dibromo-3-fluoro-2-methylbenzoic acid 11916–27-7 Otsuka Pharmaceutical 98.79 JISHA
63 Sodium 4,6-dibromo-3-fluoro-2-methylbenzoate NR Otsuka Pharmaceutical 91.79 JISHA
64 Ethyl 2-(4,6-dibromo-3-fluoro-2-methyl benzoyl)-3-cyclopropylaminopropenoate NR Otsuka Pharmaceutical 99.95 JISHA
65 Ethyl 2-(4,6-dibromo-3-fluoro-2-methylbenzoyl)-3-ethoxypropenoate NR Otsuka Pharmaceutical 100 JISHA
66 Cinnamyl 3-aminocrotonate 113898–97-8 Otsuka Pharmaceutical 98.4 JISHA
67 Cinnamyl acetoacetate 57582–46-4 Otsuka Pharmaceutical 99.4 JISHA
68 Benzyl hydrogen isophthalate 113266–88-9 Otsuka Pharmaceutical 100 JISHA
69 Sodium benzyl isophthalate NR Otsuka Pharmaceutical 95.1 JISHA
70 Dibenzyl isophthalate 16034–14-3 Otsuka Pharmaceutical 99 JISHA
71 Diethyl phosphoryl chloride 814–49-3 Tokyo Chemical Industry 99 BML
72 Bis(diphenylphosphino)ferrocene 12150–46-8 Hokko Chemical 99.4 BML
73 Phosphorus (III) bromide 7789–60-8 Tokyo Chemical Industry 98 BML
74 Triethyl phosphonoacetate 867–13-0 Tokyo Chemical Industry 98.4 BML
75 Dicyclohexyl(2′,6′-dimethoxybiphenyl-2-yl)phosphine 657408–07-6 Johnson Matthey 100 BML
76 2-Dicyclohexylphosphino-2′,4′,6′-triisopropylbiphenyl (XPhos) 564483–18-7 Mitsubishi Tanabe Pharma 99.87 Koei Techno
77 Zinc cyanide 557–21-1 Alfa Aesar 98.9 BSRC
78 3-Cyano-2,6-dihydroxypyidine monosodium salt 91467–46-8 Otsuka Pharmaceutical 98.3 JISHA
79 3-Cyano-2,6-dihydroxypyridine 35441–10-2 Otsuka Pharmaceutical 99.8 JISHA
80 6-Benzoyloxy-3-cyano-2-hydroxypyridine 103941–70-4 Otsuka Pharmaceutical 100 JISHA
81 Ethyl oxoacetate 924–44-7 Weylchem 99.7 FDSC
82 2-Fluoro-3-hydroxy-5-methoxybenzaldehyde 883576–31-6 Eisai 99.3 UBE
83 4-Bromobenzaldehyde 1122-91-4 Tokyo Chemical Industry 99.9 FDSC
84 4-Pentyn-1-ol 5390-04-5 Avra Synthesis 97.85 LSI Medience
85 (tert-Butoxycarbonyl)hydrazide 870–46-2 Shanghai Unibest Biopharma 84.8 BML
86 4,6-Dibromo-3-methoxycarbonyl-2-methylbenzenediazonium tetrafluoroborate NR Otsuka Pharmaceutical 93.2 JISHA
87 9-Fluorenylmethyl alcohol 24324–17-2 Tokyo Chemical Industry 99.9 BSRC
88 N-(3-Dimethylaminopropyl)-N′-ethylcarbodiimide HCl 25952–53-8 Toyobo 99 BML
89 Benzamidoxime 613–92-3 Shionogi >  98 Koei Techno
90 Carbethoxymethyl-dimethylsulfonium bromide 5187-82-6 Apollo Scientific 96.5b FDSC
91 3,4-Dihydro-2H-pyran 110–87-2 Tokyo Chemical Industry 99 BML
92 (2S)-2-[(tert-Butoxycarbonyl)amino]hexanedioic acid dimethyl ester 615258–01-0 Eisai 96.9 UBE
93 tert-Butyl 2-acryloylhydrazine-1-carboxylate 28689–14-7 Eisai 99.9 UBE
94 [4-(Hydroxymethyl)-2,6-dimethoxyphenyl]boronic acid 332394–37-3 Eisai 99.9 UBE
95 Triethylsilane 617–86-7 Tokyo Chemical Industry > 98 BML
96 1,3-Butanediol 107–88-0 Daicel 99.8 Nihon Bioresearch
97 Ammonium acetate 631–61-8 Wako Pure Chemical Industries 100 CERI
98 p-Toluenesulfinic acid sodium salt 7257-26-3 Tokyo Chemical Industry 99.7 BML
99 2,2,6,6-Tetramethylpiperidine 1-oxyl (free radical) 2564-83-2 Tokyo Chemical Industry 99.7 SNBL
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BSRC Biosafety Research Center, Foods, Drug and Pesticides, CERI Chemicals Evaluation and Research Institute, FDSC Hatano Research Institute, Food and Drug Safety Center, JISHA Japan Industrial Safety and Health Association, SNBL Shin Nippon Biomedical Laboratories, UBE UBE Scientific Analysis Laboratory, NR not registered

aPubChem Compound ID

bpurified after purchase

Table 2.

Chemical ID, chemical name, chemical structure, solvent used, Ames test result, and in silico analysis

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S9 fraction, prepared from the liver of phenobarbital/5,6-benzoflavone-pretreated male Sprague-Dawley rats, was purchased from Oriental Yeast (Tokyo, Japan) or Kikkoman Biochemifa (Chiba, Japan). The S9 mix consisted of 10% (v/v) S9 fraction (approximately 1.0 mg protein/plate), 8 mM MgCl2, 33 mM KCl, 5 mM glucose-6-phosphate, 4 mM NADPH, 4 mM NADH, and 100 mM sodium phosphate (pH 7.4).

Bacterial strains

Four strains of Salmonella typhimurium, namely TA100, TA1535, TA98, and TA1537, and one strain of Escherichia coli, either WP2uvrA or WP2uvrA/pKM101 (for chemical IDs 21, 56, 58, 82, 93, and 94), were used in each Ames test. Chemical ID 57 was tested using only TA100, TA98, and WP2uvrA. These tester strains are recommended for use in bacterial mutagenicity test by the Organisation for Economic Cooperation and Development (OECD) test guideline 471 [3].

Ames test

All Ames tests were conducted using the preincubation method [9, 10]. Briefly, frozen stock cultures of each strain were inoculated into a conical flask or L-tube containing nutrient broth medium (2.5% w/v; Oxoid Nutrient Broth No.2, Hampshire, UK), and then cultured in a shaking incubator at 37 °C to obtain bacterial cells in the early stationary phase. The cell density of each culture was confirmed to be > 1 × 109 cells/mL. For the tests carried out in the absence of S9 mix, 0.1 mL of the negative (vehicle) control solution, test chemical solution at various concentrations, or positive control solution was added to a test tube, to which 0.5 mL of 100 mM sodium phosphate buffer (pH 7.4) and 0.1 mL of bacterial culture were added. For the tests carried out in the presence of S9 mix, S9 mix was added in place of phosphate buffer. After mixing, the test tubes were preincubated at 37 °C for 20 min in a shaking water bath. After completion of the preincubation, the treatment mixture was immediately added and mixed with 2 mL of 0.05 mM L-histidine/0.05 mM D-biotin molten top agar (for Salmonella strains) or 0.05 mM L-tryptophan (for E. coli strains), and the content was poured onto a plate of minimal-glucose agar medium. The plates were incubated at 37 °C for approximately 48 h, and the revertant colonies that appeared were counted. The sign of bacterial background lawn was examined as an indicator of cytotoxicity. In addition, the presence or absence of a precipitate of the test chemical was checked. When acetone, tetrahydrofuran, N,N-dimethylformamide, or 1,4-dioxane was used as the solvent, 0.05 mL of the vehicle was added to the test tube.

Multiple tests (dose-finding test, main test, or confirmatory test) were conducted for 86 chemicals. For 13 chemicals, a single test was conducted, and a clear conclusion was drawn. All tests were carried out in duplicate (two plates per dose) or triplicate (three plates per dose), except for chemical ID 96 in dose-finding tests (single plate per dose). All solvents used were of high purity and were appropriate for use in Ames test.

Ames test data were generated in-house or in several Japanese contract research organizations in compliance with the Good Laboratory Practice (GLP), except for chemical IDs 47 and 57 (Table 1, Supplementary Tables).

Mutagenicity was evaluated according to the so-called “two-fold” rule [11]. The test chemical was judged to be positive (mutagenic) if the following criteria were satisfied: (1) the maximum number of revertants was two-fold or more relative to the negative (vehicle) control, (2) a dose-dependent increase in the number of revertants was observed, and (3) the results were reproducible between each test (if tests were conducted twice or thrice). Historical negative control counts in each laboratory were also considered for evaluation. Only chemical ID 4 was judged to be equivocal; although there was a clear dose-response relationship with reproducibility, the maximum number of revertants exceeded the upper limit of the historical negative control range, which was less than two-fold higher than the concurrent negative control counts.

In silico analyses

Chemicals were analyzed using a knowledge-based model [Derek Nexus (Derek), ver. 6.0.1; Lhasa Limited, Leeds, UK] and a statistics-based model (CASE Ultra, GT1_BMUT, ver. 1.8.0.2; MultiCASE Inc., OH, USA).

Results and discussion

The data for 99 chemicals, including four chemicals in the free and salt forms (chemical IDs 28 and 29, 62 and 63, 68 and 69, 78, and 79, respectively), were collected by the task force. The four pairs of these chemicals showed the same (negative) result with a similar toxicity between each pair, except for a pair of chemical IDs 28 and 29. Individual data are shown in Supplementary Tables. Table 2 lists the summarized Ames test and in silico analysis data of the test chemicals, which were arranged according to chemical classes. One-third of these chemicals were included in the training set for the latest version of CASE Ultra (where chemicals are presented as “Known positive” or “Known negative” in Table 2). The test chemicals were classified into the following chemical classes: nitrobenzenes, aromatic amines, 2-aminothiazoles, quinolinones, fluoroquinolones, pyrimidinediones, triazoles, heterocyclic compounds, sulfonyl derivatives, sulfonate esters, sulfonyl and benzoyl chlorides, halogenated alkanes, halogenated benzenes, 4,6-dibromo-3-fluoro-2-methylbenzoates, cinnamyl alcohol esters, benzoates, phosphorus-containing compounds, cyanides, aldehydes, and miscellaneous.

Structure-activity relationships

Although some chemical classes have only a few chemicals, we discuss the structure-activity (mutagenicity) relationships in relation to structural alerts.

Nitrobenzenes

The structure of nitroarenes is a representative alert for mutagenicity, although the simplest nitroarene nitrobenzene itself is not mutagenic [12–16]. All Ames-positive nitrobenzene derivatives were predicted to be mutagenic by both in silico models; however, in the present study, approximately half of the nitrobenzenes (5/9 chemicals) were non-mutagenic. The mutagenicity of nitroarenes can be generated through the reduction of the nitro moiety to the corresponding N-hydroxylamines by bacterial nitroreductase, and therefore can be efficiently detected in the absence of S9 mix [12–16]. Interestingly, chemical IDs 2–4 were mutagenic or equivocal only in the presence of S9 mix. One possible reason for nitrobenzene mutagenesis is the nitroreduction inside bacterial cells after oxidative metabolism in the S9 mix [15, 16].

Aromatic amines

The structure of aromatic amines is also a representative indicator of mutagenicity [12–14]. The primary mechanism of mutagenicity by aromatic amines is known to be the production of N-hydroxylations, typically by the CYP 1A2 enzyme, followed by O-esterification with acetate or sulfate [17, 18]. In this study, several aromatic amines (3/5 chemicals) were not mutagenic. Some substituents that generate electronic and/or steric effects probably inhibit mutagenicity through inhibition of drug-metabolizing enzymes involved and/or decreased stability of the nitrenium ion intermediate that was generated through cleavage of the N-O bond of esterified N-hydroxylamines and form adducts with DNA, leading to mutations [18, 19]. The mutagenicity of chemical ID 10 is probably due to reactive para-iminoquinone, which does not require metabolic enzymes.

2-Aminothiazoles

The 2-aminothiazoles tested, which were five-membered aromatic amines containing hetero atoms of sulfur in position 1 and nitrogen in position 3, were half mutagenic (2/4 chemicals) and half non-mutagenic (2/4 chemicals), with a diverse substituent at position 4. 2-Aminothiazoles were all predicted to be mutagenic (as “Plausible” by Derek) through identification of the structural alerts of aromatic amines or amides. 2-Aminothiazole is mutagenic, and the mutagenicity of 2-aminothiazoles is induced via the formation of reactive nitrenium ion intermediates, such as aromatic amines [19–21]. The presence of a substituent at position 4 may enhance or reduce the mutagenicity of 2-aminothiazole.

Quinolinones

The six quinolinone derivatives (chemical IDs 22–27) were non-mutagenic, whereas the other three were mutagenic. The quinolinone structure was not an alert, as shown by both in silico models. Chemical ID 19 was mutagenic, probably because of the presence of epoxide. The mutagenicity of chemical ID 20 may be derived from the dihydroxylated piperazine moiety. Chemical ID 21, an 8-hydroxy derivative of quinolinone, was mutagenic only in TA1535, and TA1537, which shows a small number of negative control counts and is empirically known to be sensitive to some structures.

Fluoroquinolones

The mutagenicity of fluoroquinolones was dependent on WP2uvrA, WP2uvrA/pKM101, or TA102, which have an AT base pair at the primary reversion site [1–3]. Fluoroquinolone antibiotics, including grepafloxacin, were reported to be mutagenic in TA102 [22] and WP2uvrA/pKM101 [23], and the positive result was used as a training set in CASE Ultra. However, in this study, where WP2uvrA was used, the three fluoroquinolone derivatives, including grepafloxacin (chemical ID 28) and grepafloxacin HCl (chemical ID 29), were all non-mutagenic.

The difference of cytotoxicity (reduction in bacterial background lawn) in the two forms (chemical IDs 28 and 29) was much more than would be expected by normal variation. It may be worth looking at the role of the different solvents, including water and DMSO.

Pyrimidinediones

The five pyrimidinedione derivatives were all non-mutagenic. Both in silico models predicted these chemicals to be inactive/negative except for one chemical called the “Out of Domain” owing to the presence of two trimethylsilyl moieties, as shown by CASE Ultra. The structure of pyrimidinedione should not be an alert for mutagenicity.

Triazoles

All three triazole derivatives were non-mutagenic. Both in silico models predicted that these chemicals were inactive/negative except for the “Inactive containing unclassified features” and “Out of Domain” owing to the presence of a tertiary amine moiety, as shown by Derek and CASE Ultra, respectively. The structure of triazole is unlikely to be an indicator of mutagenicity.

Heterocyclic compounds

The two heterocyclic compounds, derivatives of oxadiazole (chemical ID 39) and 1,3,5-triazine (chemical ID 40), were both non-mutagenic. The finding that chemical ID 39 was non-mutagenic was not consistent with the “known positive” from CASE Ultra.

Sulfonyl derivatives

The three sulfonyl derivatives were all non-mutagenic, which was consistent with that in both in silico models, although Derek identified an unclassified feature of sulfonimide in chemical ID 41. The structure of the sulfonyl moiety is not an alert for mutagenicity.

Sulfonate esters

Chemical IDs 44 and 45 were both mutagenic, and this result was consistent with the results of both in silico models. Several sulfonate esters are well-known to be alkylating mutagens, and predicted as “plausible” mutagens by Derek. However, chemical ID 46 was not mutagenic. The mutagenic potency of sulfonates is dependent on both the leaving group and alkylsulfonate moiety, affecting their chemical reaction rate [24, 25] and chemoselectivity [26, 27]. A probable reason for them being non-mutagenic is the rapid hydrolysis (instability) of ethyl trifluoromethanesulfonate [28]. The alertness of some sulfonate esters can be improved by incorporating the chemical properties.

Sulfonyl and benzoyl chlorides

The two sulfonyl chlorides (chemical IDs 47 and 48) and benzoyl chloride (chemical ID 49) were mutagenic in the presence or absence of S9 mix. Dimethyl sulfoxide (DMSO) was used as the solvent. It was reported that when DMSO was used to dissolve sulfonyl chlorides or acyl chlorides (including benzoyl chlorides), these chemicals showed mutagenicity (or false positive results) due to the generation of mutagenic impurity (chlorodimethyl sulfide) in the test chemical formulations, with a few exceptions [29, 30]. Derek predicted sulfonyl and benzoyl chlorides to be equivocal, the definition of which is that there is evidence for and against being mutagenic. These chemicals may not be mutagenic with organic solvents other than DMSO, such as acetone, where sulfonyl and acyl chlorides are stable. Water is probably not appropriate as a solvent, because these chemicals are generally unstable. Further tests on chemical IDs 47–49 are necessary to draw the correct conclusions. Nevertheless, the data presented here may be valuable as data examples when using solvents inappropriate for this chemical class. The other two benzoyl chlorides, chemical IDs 50 and 51, were correctly judged to be non-mutagenic and dissolved in acetone.

Halogenated alkanes

Halogenated alkanes (halogen atoms excluding fluorine) can be alkylating mutagens without requiring metabolic activation. Similar to that of sulfonate esters, their mutagenic activity is dependent on the alkyl moieties and the leaving group of halogen ions. A possible reason why chemical IDs 55 and 56 were non-mutagenic is that the DNA adduct was not formed via inhibition of the SN2 reaction through steric hindrance by the bulky substituent around the carbon center adjacent to the chlorine atom. In this study, chemical ID 54 with a long alkyl chain (hexyl moiety) and a leaving group of bromine ions is marginally positive only in TA1535, which shows a low number of negative control counts in the presence of S9 mix, although n-butyl chloride with a shorter alkyl moiety is reported to be non-mutagenic [31]. Primary alkyl bromides with chains longer than the hexyl moiety are probably non-mutagenic.

Halogenated benzenes

The two halogenated benzenes were non-mutagenic. Chemical ID 57 was tested with three test strains, TA100, TA98, and WP2uvrA; the strains TA100 and TA98 were most sensitive among the five strains that are recommended for use by OECD test guideline 471 [3]. Halogenated benzenes are unlikely to be structural alerts for mutagenicity, as supported by Derek.

4,6-Dibromo-3-fluoro-2-methylbenzoates

Five 4,6-dibromo-3-fluoro-2-methylbenzoate derivatives (chemical IDs 61 to 65) were non-mutagenic, and Derek and CASE Ultra did not show alerts for this structure. Therefore, the structure of 4,6-dibromo-3-fluoro-2-methylbenzoate is not an indicator of mutagenicity. The mutagenicity of chemical ID 59 might involve the enol (tautomerized) form of the 1,3-diketone moiety, followed by epoxidation of the double bond by the drug-metabolizing enzyme in S9 mix. The substitution at position 2 of the 1,3-diketone moiety may inhibit tautomerization, but not lead to the induction of mutagenicity (chemical IDs 64, 65). It remains unclear why chemical ID 60 was mutagenic. Mutagenicity may be associated with the magnesium-oxygen complex.

Cinnamyl alcohol esters

Both cinnamyl esters were non-mutagenic, as predicted by both in silico models. A double bond conjugated with a benzene ring is unlikely to be a structural indicator of mutagenicity.

Benzoates

All benzoates were non-mutagenic, as predicted by both in silico models.

Phosphorus-containing chemicals

Phosphorus-containing chemicals were all non-mutagenic except for chemical ID 71, which is electrophilic and routinely used in organic synthesis for the phosphorylation of amines [32]. For many of the phosphorus-containing chemicals tested, neither of the in silico models were able to make a definite, positive/negative prediction; the reference to negative by Derek contained unclassified features, and CASE Ultra called “Out of Domain”. This indicates that phosphorus-containing chemicals are outside the applicability domain because of the limited number of training set examples for each in silico model.

Cyanides

Cyanide ion (Chemical ID 77) and all the cyanide derivatives substituted with an aromatic ring were non-mutagenic. The cyanide moiety is unlikely to be a structural alert for mutagenicity, as supported by Derek.

Aldehydes

Chemical ID 81, an aldehyde conjugated with a single carbonyl moiety, was mutagenic, as predicted by both in silico models. The chemical properties of aldehydes largely differ between aliphatic and aromatic compounds; generally, the former is chemically reactive, whereas the latter is stable. Both aromatic aldehydes (chemical IDs 82 and 83) were non-mutagenic, which can be explained by the extremely low chemical reactivity of aromatic aldehydes.

Miscellaneous

The miscellaneous group consists of chemicals that cannot be simply classified into the above chemical classes. Many of the chemicals tested were non-mutagenic. Chemical ID 84 was mutagenic in the presence and absence of S9 mix, although there were no structural alerts identified by Derek. The cause of the mutagenicity is unclear, but aldehyde might be involved in the induction of mutagenicity, which may be generated from alcohol by the alcohol dehydrogenase present in bacteria [33]. The three chemicals (chemical IDs 85–87) were mutagenic. Chemical IDs 85 and 86 were mutagenic only in WP2uvrA and TA1535, respectively. Both chemicals were predicted to be mutagenic (Derek; Plausible, CASE Ultra; Inconclusive or Positive) by both in silico models. Chemical ID 87 was only mutagenic in TA1537, which would be a tester strain sensitive to some chemical structures, with a small number of negative control counts.

In silico analyses

To calculate the sensitivity, specificity, and accuracy of in silico predictions, ten chemicals (chemical IDs 29, 47–49, 57, 60, 63, 69, 78, and 99) were excluded. Four chemicals tested in both forms were used for calculation in the free form (chemical IDs 28, 62, 68, and 79), but not in the salt form (chemical IDs 29, 63, 69, and 78). Chemical IDs 47–49 were false positive because probable inappropriate solvents were used. Chemical ID 57 was tested in only three strains (TA100, TA98 and WP2uvrA). For chemical IDs 60 and 99, the in silico models could not reach a conclusion because the former is a complex molecule and the latter is a radical. We treated “Out of Domain” fragments as well as “Inconclusive”, “Equivocal”, “Inactive (contains misclassified or unclassified features)”, as neither Ames-positive nor Ames-negative in this study.

In silico analysis using Derek (ver. 6.0.1) revealed the sensitivity, specificity, and accuracy to be 65% (15/23), 71% (47/66), and 70% (62/89), respectively. In contrast, in silico analysis using CASE Ultra (GT1_BMUT, ver. 1.8.0.2) revealed the sensitivity, specificity, and accuracy to be 50% (6/12), 60% (25/42), and 57% (31/54), respectively. Thus, Derek outperformed CASE Ultra (GT1_BMUT) in the predictive level of bacterial mutagenicity for all the parameters in this study, where the limited number of chemicals were compared.

Derek and Case Ultra occasionally called “inactive containing misclassified or unclassified features” (8 chemicals), and “Out of Domain” fragments (10 chemicals), respectively, indicating the need to expand the training or reference set for each in silico model to improve.

It is worth noting that when considering the performance of the in silico models, it is important to account for the ICH M7 approach of combining two complementary systems and an expert review to take a final decision rather than considering them separately [5, 34].

Inconsistency with training set examples

The 35 chemicals (15 “known” positives and 20 “known” negatives) were part of the training set for CASE Ultra. The results for 4 of 35 chemicals (11%) did not agree with the known response for those chemicals in that training set. The four chemicals (chemical IDs 28, 39, 88, and 89) were non-mutagenic but were registered as mutagens in the training set for CASE Ultra. This disagreement ratio (11%) was in the same range as the Ames test non-reproducibility, identified by Piegorsch and Zeiger, who reported a value of approximately 13% [35]. The reasons why the Ames test evaluations did not match were mainly some differences in the test conditions (e.g., plate-incorporation method vs. preincubation method, the type of strains used, source of test strains, preparation of overnight culture), and evaluation criteria (e.g., two-fold rule vs. statistical analysis), and quality of test substances [10, 11, 36].

Two chemicals (chemical IDs 47 and 48) were mutagenic but were registered as non-mutagens in the CASE Ultra training set. This is probably because the solvent used in our study was not appropriate, as previously stated (see the section of “Sulfonyl and benzoyl chlorides” in the Structure-activity relationships section. Our data, together with individual data (Supplementary Tables), provide additional information and will help in reevaluating the Ames test data.

Test strains to detect bacterial mutagens

In this study, 28 chemicals, including three sulfonyl and benzoyl chlorides (chemical IDs 47 to 49) were mutagenic. Among them, three chemicals (chemical IDs 16, 54, and 86), two chemicals (chemical IDs 21 and 87), two chemicals (chemical IDs 53 and 85), and two chemicals (chemical IDs 49 and 60), respectively, were only detected for mutagenicity in either TA1535, TA1537, WP2uvrA, or both TA1535 and WP2uvrA. Williams et al. [36] reported that 93% of bacterial mutagens can be detected with a combination of TA100 and TA98. However, the data of the present study show that only 19 out of 28 chemicals (68%) were detected either by TA100 or TA98. Therefore, the test strains TA1535, TA1537, and WP2uvrA may be useful for the efficient detection of bacterial mutagenicity.

Conclusion

Ames test data were presented for 99 chemicals from eight pharmaceutical companies through the activity of the Ames data sharing task force. The chemicals were related to the manufacturing process of pharmaceutical drugs, including reagents, synthetic intermediates, and drug substances. The Ames test data presented herein will contribute to avoiding duplicated Ames test in some cases, supporting duplicate testing in other cases, improving in silico models, and enhancing our understanding of the mechanisms of mutagenesis.

Supplementary Information

Additional file 1. (1.6MB, xlsx)

Acknowledgments

We are grateful to Dr. K. Koyama and M. Kurakami of Eisai Co., Ltd. for the in silico analyses and helpful comments on the manuscript, respectively. We would like to thank Editage (www.editage.com) for English language editing.

Abbreviations

9AA

9-aminoacridine

2AA

2-aminoanthracene

B[a]P

Benzo[a]pyrene

ICR-191

6-chloro-9-[3-(2-chloroethylamino)propylamino]-2-methoxyacridine dihydrochloride

DMSO

Dimethyl sulfoxide

AF-2

2-(2-furyl)-3-(5-nitro-2-furyl)​acrylamide

GLP

Good Laboratory Practice

ICH

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use

JPMA

Japan Pharmaceutical Manufacturers Association

OECD

Organisation for Economic Cooperation and Development

Authors’ contributions

AH analyzed the chemicals using Derek and drafted and edited the manuscript. AH, TA, TS, AO, MY, KK, HO, YD, SO, KS, TK, and EY prepared the Supplementary Tables and reviewed the manuscript. All authors approved the final manuscript.

Funding

All Ames tests were funded or sponsored by each company that participated in this task force. Funding for open access to this publication was provided by the Japan Pharmaceutical Manufacturers Association.

Availability of data and materials

All Ames data are available in the Supplementary Tables. Materials are not applicable.

Declarations

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Atsushi Hakura, Email: a-hakura@hhc.eisai.co.jp.

Takumi Awogi, Email: Awogi.Takumi@otsuka.jp.

Toshiyuki Shiragiku, Email: Shiragiku.Toshiyuki@otsuka.jp.

Atsushi Ohigashi, Email: atsushi.oohigashi@astellas.com.

Mika Yamamoto, Email: mika.yamamoto@astellas.com.

Kayoko Kanasaki, Email: kayoko.kanasaki@shionogi.co.jp.

Hiroaki Oka, Email: hiro-oka@taiho.co.jp.

Yasuaki Dewa, Email: yasuaki.dewa@mb.kyorin-pharm.co.jp.

Shunsuke Ozawa, Email: shunsuke.ozawa@mb.kyorin-pharm.co.jp.

Kouji Sakamoto, Email: ko-sakamoto@taisho.co.jp.

Tatsuya Kato, Email: katou.tatsuya@ma.mt-pharma.co.jp.

Eiji Yamamura, Email: yamamura.eiji@md.mt-pharma.co.jp.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Additional file 1. (1.6MB, xlsx)

Data Availability Statement

All Ames data are available in the Supplementary Tables. Materials are not applicable.

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