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Contamination of drug products and substances containing impurities is a significant concern in the pharmaceutical industry because it may impact the quality and safety of medicinal products. Special attention is required when mutagenic impurities are present in pharmaceuticals, as they may pose a risk of carcinogenicity to humans. Therefore, controlling potential mutagenic impurities in active pharmaceutical ingredients to an acceptable safety limit is mandatory to ensure patient safety. As per the International Council for Harmonization (ICH) M7 (R2) 3 Guideline, mutagenic impurities are those compounds or materials that induce point mutations. In 2018, the sartan class of drugs was recalled due to the presence of N-nitrosamine impurities, which are potential mutagens. In addition to the primary impurities being detected, this class of products, especially losartan, irbesartan and valsartan, have been identified as having organic azido contaminants, which are again highly reactive toward DNA, leading to an increased risk of cancer. These azido impurities form during the preparation of the tetrazole moiety via the reaction of a nitrile intermediate with sodium azide. Given that this is a newly raised issue in the pharmaceutical world, it should be noteworthy to review the related literature. Thus, this review article critically accounts for (i) the toxicity of azido impurities and the proposed mechanism of mutagenicity, (ii) the regulatory perspective, and (iii) the sources and control strategies used during the preparation of drug substances and (iv) future perspectives., (© 2024. The Author(s), under exclusive licence to The Drug Information Association, Inc.)

Photooxidation products resulting from volatile organic compounds (VOCs) reacting with sunlight are important contributors to gas-phase air pollution. We characterized the product-weighted mutagenic potencies (rev m 3 mgC -1 h -1 ) in Salmonella TA100 of atmospheres resulting from the hydroxyl radical (OH)-initiated photochemical oxidation of 11 C 4 or C 5 alkenes or dienes in the presence of nitric oxide (NO) and from the ozonolysis of four VOCs without NO (isoprene; 1,3-pentadiene; 1,4-pentadiene; and 1,3-butadiene). Irradiated atmospheres from precursors with a single C═C bond (3-methyl-1-butene, 2-methyl-1-butene, cis/trans -2-pentene, 2-methyl-2-butene, 1-butene, and 1-pentene) had low potencies (<5), whereas linear dienes with terminal C═C bonds had high potencies (50-65). Dienes with a branched structure (isoprene) or internal C═C bonds (1,3-pentadiene) had intermediate potencies (15-20). No VOCs were mutagenic without photochemical oxidation. VOCs+O 3 in the dark produced less mutagenic atmospheres than photochemistry in the presence of NO. Atmospheres induced primarily C to T and C to A mutations, the main base substitutions in nonsmoker lung cancer. Atmospheres from the photooxidation of isoprene and 1,3-pentadiene also induced GG to TT, the signature mutation of peroxyacetyl nitrate. Five molecular compositions identified by Chemical Ionization Mass Spectrometry (CIMS), most containing nitrogen, correlated ( r = 0.76-0.85) with the mutagenic potencies of irradiated atmospheres; most had a likely nitrate functional group. Assessment of the mutagenicity of emitted VOCs should consider VOC photooxidation products, especially dienes with terminal C═C bonds, as these products likely contribute to overall health effects from ambient air pollution.

This study assessed the presence of the genotoxic impurity 1-methyl-4-nitrosopiperazine (MNP) in 27 batches of rifampicin capsules obtained from 11 manufacturers in China. While they were below the temporary limit of 5 ppm set by the US Food and Drug Administration, the observed levels (0.33-2.36 ppm) exceeded the acceptable threshold of 0.16 ppm. Building upon preliminary findings and degradation experiments, we concluded that MNP is a by-product of the oxidative degradation of rifampicin or is introduced via oxidation or nitrosation during the synthesis process involving 1-methyl-4-aminopiperazine. The pathways of MNP formation were confirmed in this study. Furthermore, we observed that the addition of antioxidants, sealed storage, and selection of dominant crystal forms can aid in controlling MNP levels., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Utilizing molecular dynamics and free energy perturbation, we examine the relative binding affinity of several covalent polycyclic aromatic hydrocarbon - DNA (PAH-DNA) adducts at the central adenine of NRAS codon-61, a mutational hotspot implicated in cancer risk. Several PAHs classified by the International Agency for Research on Cancer as probable, possible, or unclassifiable as to carcinogenicity are found to have greater binding affinity than the known carcinogen, benzo[a]pyrene (B[a]P). van der Waals interactions between the intercalated PAH and neighboring nucleobases, and minimal disruption of the DNA duplex drive increases in binding affinity. PAH-DNA adducts may be repaired by global genomic nucleotide excision repair (GG-NER), hence we also compute relative free energies of complexation of PAH-DNA adducts with RAD4-RAD23 (the yeast ortholog of human XPC-RAD23) which constitutes the recognition step in GG-NER. PAH-DNA adducts exhibiting the greatest DNA binding affinity also exhibit the least RAD4-RAD23 complexation affinity and are thus predicted to resist the GG-NER machinery, contributing to their genotoxic potential. In particular, the fjord region PAHs dibenzo[a,l]pyrene, benzo[g]chrysene, and benzo[c]phenanthrene are found to have greater binding affinity while having weaker RAD4-RAD23 complexation affinity than their respective bay region analogs B[a]P, chrysene, and phenanthrene. We also find that the bay region PAHs dibenzo[a,j]anthracene, dibenzo[a,c]anthracene, and dibenzo[a,h]anthracene exhibit greater binding affinity and weaker RAD4-RAD23 complexation affinity than B[a]P. Thus, the study of PAH genotoxicity likely needs to be substantially broadened, with implications for public policy and the health sciences. This approach can be broadly applied to assess factors contributing to the genotoxicity of other unclassified compounds., Competing Interests: Competing interests statement:NSF grant CHE-2203366.

Despite intensive search over the past decades, only a few small-molecule DNA fluorescent dyes were found with large Stokes shifts. These molecules, however, are often too toxic for widespread usage. Here, we designed DNA-specific fluorescent dyes rooted in benzimidazole architectures with a hitherto unexplored molecular framework based on thiazole-benzimidazole scaffolding. We further incorporated a pyrazole ring with an extended sidechain to prevent cell penetration. These novel benzimidazole derivatives were predicted by quantum calculations and subsequently validated to have large Stokes shifts ranging from 135 to 143 nm, with their emission colors changed from capri blue for the Hoechst reference compound to iguana green. These readily-synthesized compounds, which displayed improved DNA staining intensity and detection limits along with a complete loss of capability for cellular membrane permeation and negligible mutagenic effects as designed, offer a safer alternative to the existing high-performance small-molecule DNA fluorescent dyes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Nitroaromatic compounds (NACs) stand out as pervasive organic pollutants, prompting an imperative need to investigate their hazardous effects. Computational chemistry methods play a crucial role in this exploration, offering a safer and more time-efficient approach, mandated by various legislations. In this study, our focus lay on the development of transparent, interpretable, reproducible, and publicly available methodologies aimed at deriving quantitative structure-activity relationship models and testing them by modelling the mutagenicity of NACs against the Salmonella typhimurium TA100 strain. Descriptors were selected from Mordred and RDKit molecular descriptors, along with several quantum chemistry descriptors. For that purpose, the genetic algorithm (GA), as the most widely used method in the literature, and three alternative algorithms (Boruta, Featurewiz, and ForwardSelector) combined with the forward stepwise selection technique were used. The construction of models utilized the multiple linear regression method, with subsequent scrutiny of fitting and predictive performance, reliability, and robustness through various statistical validation criteria. The models were ranked by the Multi-Criteria Decision Making procedure. Findings have revealed that the proposed methodology for descriptor selection outperforms GA, with Featurewiz showing a slight advantage over Boruta and ForwardSelector. These constructed models can serve as valuable tools for the quick and reliable prediction of NACs mutagenicity., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Potential genotoxic impurities in medications are an increasing concern in the pharmaceutical industry and regulatory bodies because of the risk of human carcinogenesis. To prevent the emergence of these impurities, it is crucial to carefully examine not only the final product but also the intermediates and key starting material (KSM) used in drug synthesis. During the related substances analysis of KSM of Famotidine, an unknown impurity in the range of 0.5-1.0% was found prompting the need for isolation and characterization due to the possibility of its to infiltrate into the final product. In this study, the impurity was isolated and characterized as 5-(2-chloroethyl)-3,3-dimethyl-3,4-dihydro-2H-1,2,4,6-thiatriazine 1,1-dioxide using multiple instrumental analysis, uncovering a structural alert that raises concern. Considering the potential impact of impurity on human health, an in silico genotoxicity assessment was established using Derek and Sarah tool in accordance with ICH M7 guideline. Furthermore, molecular docking and molecular dynamics simulation were performed to evaluate the specific interaction of the impurity with DNA. The findings reveal consistent interaction of the impurity with the dG-rich region of the DNA duplex and binding at the minor groove. Both in silico prediction and molecular dynamic study confirmed the genotoxic character of the impurity. The newly discovered impurity in famotidine has not been reported previously, and there is currently no analytical method available for its identification and control. A highly sensitive HPLC-UV method was developed and validated in accordance with ICH requirements, enabling quantification of the impurity at trace level in famotidine ensuring its safe release.

The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecules. However, experimental mutagenicity testing can be time-consuming and costly. One solution to reduce the annotation cost is active learning, where the algorithm actively selects the most valuable molecules from a vast chemical space and presents them to the oracle (e.g., a human expert) for annotation, thereby rapidly improving the model's predictive performance with a smaller annotation cost. In this paper, we propose muTOX-AL, a deep active learning framework, which can actively explore the chemical space and identify the most valuable molecules, resulting in competitive performance with a small number of labeled samples. The experimental results show that, compared to the random sampling strategy, muTOX-AL can reduce the number of training molecules by about 57%. Additionally, muTOX-AL exhibits outstanding molecular structural discriminability, allowing it to pick molecules with high structural similarity but opposite properties., (© 2024. The Author(s).)

Chemicals often require metabolic activation to become genotoxic. Established test guidelines recommend the use of the rat liver S9 fraction or microsomes to introduce metabolic competence to in vitro cell-based bioassays, but the use of animal-derived components in cell culture raises ethical concerns and may lead to quality issues and reproducibility problems. The aim of the present study was to compare the metabolic activation of cyclophosphamide (CPA) and benzo[ a ]pyrene (BaP) by induced rat liver microsomes and an abiotic cytochrome P450 (CYP) enzyme based on a biomimetic porphyrine catalyst. For the detection of genotoxic effects, the chemicals were tested in a reporter gene assay targeting the activation of the cellular tumor protein p53. Both chemicals were metabolized by the abiotic CYP enzyme and the microsomes. CPA showed no activation of p53 and low cytotoxicity without metabolic activation, but strong activation of p53 and increased cytotoxicity upon incubation with liver microsomes or abiotic CYP enzyme. The effect concentration causing a 1.5-fold induction of p53 activation was very similar with both metabolization systems (within a factor of 1.5), indicating that genotoxic metabolites were formed at comparable concentrations. BaP also showed low cytotoxicity and no p53 activation without metabolic activation. The activation of p53 was detected for BaP upon incubation with active and inactive microsomes at similar concentrations, indicating experimental artifacts caused by the microsomes or NADPH. The activation of BaP with the abiotic CYP enzyme increased the cytotoxicity of BaP by a factor of 8, but no activation of p53 was detected. The results indicate that abiotic CYP enzymes may present an alternative to rat liver S9 fraction or microsomes for the metabolic activation of test chemicals, which are completely free of animal-derived components. However, an amendment of existing test guidelines would require testing of more chemicals and genotoxicity end points.

Sulfonate esters, one class of genotoxic impurities (GTIs), have gained significant attention in recent years due to their potential to cause genetic mutations and cancer. In the current study, we employed the dummy template molecular imprinting technology with a dummy template molecule replacing the target molecule to establish a pretreatment method for samples containing p-toluene sulfonate esters. Through computer simulation and ultraviolet-visible spectroscopy analysis, the optimal functional monomer acrylamide and polymerization solvent chloroform were selected. Subsequently, a dummy template molecularly imprinted polymer (DMIP) was prepared by the precipitation polymerization method, and the polymer was characterized in morphology, particle size, and composition. The results of the adsorption and enrichment study demonstrated that the DMIP has high adsorption capability (Q = 7.88 mg/g) and favorable imprinting effects (IF = 1.37); Further, it could simultaneously adsorb three p-toluene sulfonate esters. The optimal adsorption conditions were obtained by conditional optimization of solid-phase extraction (SPE). A pH 7 solution was selected as the loading condition, the methanol/1 % phosphoric acid solution (20:80, v/v) was selected as the washing solution, and acetonitrile containing 10 % acetic acid in 6 mL was selected as the elution solvent. Finally, we determined methyl p-toluene sulfonate alkyl esters, ethyl p-toluene sulfonate alkyl esters, and isopropyl p-toluene sulfonate alkyl esters in tosufloxacin toluene sulfonate and capecitabine at the 10 ppm level (relative to 1 mg/mL active pharmaceutical ingredient (API) samples) by using DMIP-based SPE coupled with HPLC. This approach facilitated the selective enrichment of p-toluene sulfonate esters GTIs from complex API samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the present study, we investigated the genotoxicity of the active products formed from N-nitrosoproline (NPRO) dissolved in oleic acid following ultraviolet A (UVA) irradiation, bypassing the need for metabolic activation. We previously demonstrated the photomutagenicity of NPRO dissolved in a phosphate-buffered solution. It has been suggested that the association of the nitrosamine group with acid ions facilitates rapid photodissociation and photoactivation. We hypothesized that NPRO's inherent carboxyl group may mimic an acid, inducing photodissociation and photomutagenicity, even in a non-aqueous solvent lacking acidic ions. Following UVA irradiation, NPRO dissolved in oleic acid exhibited a dose-dependent mutagenic activity. Similar results were obtained when NPRO was dissolved in linoleic acid and triolein. Nitric oxide formation, which is dependent on NPRO concentration, is accompanied by mutagenic activity. The mutagenicity spectrum obtained in response to NPRO irradiation followed the absorption curve of NPRO dissolved in oleic acid. Irradiated NPRO in oleic acid displayed relative stability, retaining approximately 18, 36, and 63 % of initial mutagenicity after 10 days of storage at 25, 4, and -20 °C, respectively. Thus NPRO stored in a fatty environment undergoes photoactivation upon irradiation, leading to genotoxicity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In dietary risk assessment of plant protection products, residues of active ingredients and their metabolites need to be evaluated for their genotoxic potential. The European Food Safety Authority recommend a tiered approach focussing assessment and testing on classes of similar chemicals. To characterise similarity, in terms of metabolism, a metabolic similarity profiling scheme has been developed from an analysis of 69 α-chloroacetamide herbicides for which either Ames, chromosomal aberration or micronucleus test results are publicly available. A set of structural space alerts were defined, each linked to a key metabolic transformation present in the α-chloroacetamide metabolic space. The structural space alerts were combined with covalent chemistry profiling to develop categories suitable for chemical prioritisation via read-across. The method is a robust and reproducible approach to such read-across predictions, with the potential to reduce unnecessary testing. The key challenge in the approach was identified as being the need for metabolism data individual groups of plant protection products as the basis for the development of the structural space alerts., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Zuzana Hasarova reports financial support was provided by Crop Life Europe., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The detection of aromatic aldehydes, considered potential genotoxic impurities, holds significant importance during drug development and production. Current analytical methods necessitate complex pre-treatment processes and exhibit insufficient specificity and sensitivity. This study presents the utilization of naphthalenediimide as a pre-column derivatisation reagent to detect aromatic aldehyde impurities in pharmaceuticals via high-performance liquid chromatography (HPLC). We screened a series of derivatisation reagents through density functional theory (DFT) and investigated the phenomenon of photoinduced electron transfer (PET) for both the derivatisation reagents and the resulting products. Optimal experimental conditions for derivatisation were achieved at 40 °C for 60 min. This approach has been successfully applied to detect residual aromatic aldehyde genotoxic impurities in various pharmaceutical preparations, including 4-Nitrobenzaldehyde, 2-Nitrobenzaldehyde, 1,4-Benzodioxane-6-aldehyde, and 5-Hydroxymethylfurfural. The pre-column derivatisation method significantly enhanced detection sensitivity and reduced the limit of detection (LOD), which ranged from 0.002 to 0.008 μg/ml for the analytes, with relative standard deviations < 3 %. The correlation coefficient (R 2 ) >0.998 demonstrated high quality. In chloramphenicol eye drops, the concentration of 4-Nitrobenzaldehyde was measured to be 8.6 µg/mL below the specified concentration, with recoveries ranging from 90.0 % to 119.2 %. In comparison to existing methods, our work simplifies the pretreatment process, enhances the sensitivity and specificity of the analysis, and offers comprehensive insights into impurity detection in pharmaceutical preparations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Vigabatrin (VGB) is a gammaaminobutyric acid-ergic (GABA-ergic) antiepileptic drug (AED) and is one of 2 approved drugs available to treat infantile spasms (IS). The aim of this study is to elucidate conflicting data on the toxic effects of VGB and to obtain detailed information about its possible cytogenotoxic effects in human lymphocytes. For this purpose, in vitro Chromosomal Aberration (CA), Sister Chromatid Exchange (SCE), Micronucleus (MN) tests, and Comet Assay were performed to determine possible genotoxic and cytotoxic effects of VGB. In addition, the binding energy level of VGB to DNA was determined in silico by molecular docking. The highest concentration (80 μg/ml) of VGB increased the SCE, CA, MN and micronucleated binuclear cell (BNMN) frequency significantly compared to the control after 24 and 48 hours of treatment. In the tail density and tail length parameters, the dose-dependent increase was found to be statistically significant compared to the control. At the 40 and 80 μg/ml concentrations of VGB for 48 hours caused a statistically significant increase in both CA/Cell and AC percentages, while MI and NDI decreased only significantly at the highest concentration (80 µg/ml) causing. In the Comet Assay head density, tail density and tail length parameters, the dose-dependent increase was found to be statistically significant compared to the control. Also, the in silico molecular docking analysis showed that VGB interacts with B-DNA close to the threshold binding energy. The lowest negative free binding energy (ΔG binding) was found as -5.13 kcal/mol. In conclusion, all results are evaluated together, it has been determined that VGB has cytogenotoxic effects in vitro and binds to DNA in silico with significant free binding energy.

Structural alerts (SAs) are essential to identify chemicals for toxicity evaluation and health risk assessment. We constructed a novel SMILES split-based deep learning model (SSDL) that was trained and verified with 5850 chemicals from the ISSSTY database and 384 external test chemicals from published papers. The training accuracy was above 0.90 and the evaluation metrics (precision, recall and F1-score) all reached 0.78 or above on both internal and external test chemicals. In this model, the molecular-specific fragment importance of chemicals was first quantified independently. Then, the SA identification method based on the importance of these fragments was statistically analyzed and verified with the ISSSTY test and external test chemicals containing one of 28 typical SAs, and most of the performances were better than that of expert rules. Furthermore, a mutagenicity mechanism prediction method was developed using 237 chemicals with four known mutagenic mechanisms based on molecular similarity calibrated by the SSDL method and fragment importance, which significantly improved accuracy in three mechanisms and had comparable accuracy in the other one compared to traditional methods. Overall, the SSDL model quantifying fragment toxicity within molecules would be a novel potentially powerful tool in the determination and visualization of molecular-specific SAs and the prediction of mutagenicity mechanisms for environmental or industrial compounds and drugs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The robust control of genotoxic N-nitrosamine (NA) impurities is an important safety consideration for the pharmaceutical industry, especially considering recent drug product withdrawals. NAs belong to the 'cohort of concern' list of genotoxic impurities (ICH M7) because of the mutagenic and carcinogenic potency of this chemical class. In addition, regulatory concerns exist regarding the capacity of the Ames test to predict the carcinogenic potential of NAs because of historically discordant results. The reasons postulated to explain these discordant data generally point to aspects of Ames test study design. These include vehicle solvent choice, liver S9 species, bacterial strain, compound concentration, and use of pre-incubation versus plate incorporation methods. Many of these concerns have their roots in historical data generated prior to the harmonization of Ames test guidelines. Therefore, we investigated various Ames test assay parameters and used qualitative analysis and quantitative benchmark dose modelling to identify which combinations provided the most sensitive conditions in terms of mutagenic potency. Two alkyl-nitrosamines, N-nitrosodimethylamine (NDMA) and N-nitrosodiethylamine (NDEA) were studied. NDMA and NDEA mutagenicity was readily detected in the Ames test and key assay parameters were identified that contributed to assay sensitivity rankings. The pre-incubation method (30-min incubation), appropriate vehicle (water or methanol), and hamster-induced liver S9, alongside Salmonella typhimurium strains TA100 and TA1535 and Escherichia coli strain WP2uvrA(pKM101) provide the most sensitive combination of assay parameters in terms of NDMA and NDEA mutagenic potency in the Ames test. Using these parameters and further quantitative benchmark dose modelling, we show that N-nitrosomethylethylamine (NMEA) is positive in Ames test and therefore should no longer be considered a historically discordant NA. The results presented herein define a sensitive Ames test design that can be deployed for the assessment of NAs to support robust impurity qualifications., (© The Author(s) 2023. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society.)

5-Aminoisophthalic acid and 5-nitroisophthalic acid (5-NIPA) are potential impurities in preparations of 5-amino-2,4,6-triiodoisophthalic acid, which is a key intermediate in the synthesis of the iodinated contrast agent iopamidol. We have studied their mutagenicity in silico (quantitative structure-activity relationships, QSAR) and by the bacterial reverse mutation assay (Ames test). First, the compounds were screened with the tools Derek Nexus™ and Leadscope®. Both compounds were flagged as potentially mutagenic (class 3 under ICH M7). However, contrary to the in silico prediction, neither chemical was mutagenic in the Ames test (plate incorporation method) with or without S9 metabolic activation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

The Ames test is one of the most applied tools in mutagenicity testing of chemicals ever since its introduction by Ames et al. in the 1970s. Its principle is based on histidine auxotrophic bacteria that regain prototrophy through reverse mutations. In the presence of a mutagen, more reverse mutations occur that become visible as increased bacterial growth on medium without histidine. Many miniaturized formats of the Ames test have emerged to enable the testing of environmental water samples, increase experimental throughput, and lower the required amounts of test substances. However, most of these formats still rely on endpoint determinations. In contrast, the recently introduced Ames RAMOS test determines mutagenicity through online monitoring of the oxygen transfer rate. In this study, the oxygen transfer rate of Salmonella typhimurium TA100 during the Ames plate incorporation test was monitored and compared to the Ames RAMOS test to prove its validity further. Furthermore, the Ames RAMOS test in 96-well scale is newly introduced. For both the Ames plate incorporation and the Ames RAMOS test, the influence of the inoculum cell count on the negative control was highlighted: A lower inoculum cell count led to a higher coefficient of variation. However, a lower inoculum cell count also led to a higher separation efficiency in the Ames RAMOS test and, thus, to better detection of a mutagenic substance at lower concentrations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Quantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Second Ames/QSAR International Challenge Project (2020-2022) as a successor to the First Project (2014-2017), with 21 teams from 11 countries participating. The DGM/NIHS provided a curated training dataset of approximately 12,000 chemicals and a trial dataset of approximately 1,600 chemicals, and each participating team predicted the Ames mutagenicity of each trial chemical using various Ames/QSAR models. The DGM/NIHS then provided the Ames test results for trial chemicals to assist in model improvement. Although overall model performance on the Second Project was not superior to that on the First, models from the eight teams participating in both projects achieved higher sensitivity than models from teams participating in only the Second Project. Thus, these evaluations have facilitated the development of QSAR models.

The unexpected finding of N-nitrosamine (NA) impurities in many pharmaceutical products raised significant challenges for industry and regulators. In addition to well-studied small molecular weight NAs, many of which are potent rodent carcinogens, novel NAs associated with active pharmaceutical ingredients have been found, many of which have limited or no safety data. A tiered approach to establishing Acceptable Intake (AI) limits for NA impurities has been established using chemical-specific data, read-across, or a class-specific TTC limit. There are ∼140 NAs with some rodent carcinogenicity data, but much of it is older and does not meet current guidelines for what constitutes a 'robust' bioassay. Nevertheless, these data are an important source of information to ensure the best science is used for assessing NA impurities and assuring consumer safety while minimizing impact that can lead to drug shortages. We present several strategies to maximize the use of imperfect data including using a lower confidence limit on a rodent TD50, and leveraging data from multiple NAs. Information on the chemical structure known to impact potency can also support development of an AI or potentially conclude that a particular NA does not fall in the cohort of concern for potent carcinogenicity., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: S. Felter and A. Mudd are employed by the Procter & Gamble Company which sells consumer products including over-the-counter drugs that are subject to regulatory requirements for evaluating and ensuring safety associated with the potential for nitrosamine impurities to be present. D. Ponting, R. Thomas, and A. Oliveira are employed by Lhasa Limited and have no known competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The Ames test is a gold standard mutagenicity assay that utilizes various Salmonella typhimurium strains with and without S9 fraction to provide insights into the mechanisms by which a chemical can mutate DNA. Multitask deep learning is an ideal framework for developing QSAR models with multiple end points, such as the Ames test, as the joint training of multiple predictive tasks may synergistically improve the prediction accuracy of each task. This work investigated how toxicology domain knowledge can be used to handcraft task groupings that better guide the training of multitask neural networks compared to a naïve ungrouped multitask neural network developed on a complete set of tasks. Sixteen S. typhimurium ± S9 strain tasks were used to generate groupings based on mutagenic and metabolic mechanisms that were reflected in correlation data analyses. Both grouped and ungrouped multitask neural networks predicted the 16 strain tasks with a higher balanced accuracy compared with single task controls, with grouped multitask neural networks consistently featuring incremental increases in predictivity over the ungrouped approach. We conclude that the main variable driving these performance improvements is the general multitask effect with mechanistic task groupings acting as an enhancement step to further concentrate synergistic training signals united by a common biological mechanism. This approach enables incorporation of toxicology domain knowledge into multitask QSAR model development allowing for more transparent and accurate Ames mutagenicity prediction.

The prediction of Ames mutagenicity continues to be a concern in both regulatory and pharmacological toxicology. Traditional quantitative structure-activity relationship (QSAR) models of mutagenicity make predictions based on molecular descriptors calculated on a chemical data set used in their training. However, it is known that molecules such as aromatic amines can be non-mutagenic themselves but metabolically activated by S9 rodent liver enzyme in Ames tests forming molecules such as iminoquinones or amine substituents that better stabilize mutagenic nitrenium ions in known pathways of mutagenicity. Modern in silico modeling methods can implicitly model these metabolites through consideration of the structural elements relevant to their formation but do not include explicit modeling of these metabolites' potential activity. These metabolites do not have a known individual mutagenicity label and, in their current state, cannot be fitted into a traditional QSAR model. Multiple instance learning (MIL) however can be applied to a group of metabolites and their parent under a single mutagenicity label. Here we trained MIL models on Ames data, first with an aromatic amines data set ( n = 457), a class known to require metabolic activation, and subsequently on a larger data set ( n = 6505) incorporating multiple molecular species. MIL was shown to be able to predict Ames mutagenicity with performance in line with previously established models (balanced accuracy = 0.778), suggesting its potential utility in Ames prediction applications. Furthermore, the MIL model predicted well on identified hard-to-predict molecule groups relative to the models in which these molecule groups were identified. These results are presumably due to the increased consideration of the metabolic contribution to the mutagenic outcome. Further exploration of MIL as a supplement to existing models could aid in the prediction of chemicals where implicit modeling of metabolites cannot fully grasp their characteristics. This paper demonstrates the potential of an MIL approach to modeling Ames tests with S9 and is particularly relevant to metabolically activated xenobiotic mutagens.

Structural alerts are molecular substructures assumed to be associated with molecular initiating events in various toxic effects and an integral part of in silico toxicology. However, alerts derived using the knowledge of human experts often suffer from a lack of predictivity, specificity, and satisfactory coverage. In this work, we present a method to build hybrid QSAR models by combining expert knowledge-based alerts and statistically mined molecular fragments. Our objective was to find out if the combination is better than the individual systems. Lasso regularization-based variable selection was applied on combined sets of knowledge-based alerts and molecular fragments, but the variable elimination was only allowed to happen on the molecular fragments. We tested the concept on three toxicity end points, i.e., skin sensitization, acute Daphnia toxicity, and Ames mutagenicity, which covered both classification and regression problems. Results showed the predictive performance of such hybrid models is, indeed, better than the models based solely on expert alerts or statistically mined fragments alone. The method also enables the discovery of activating and mitigating/deactivating features for toxicity alerts and the identification of new alerts, thereby reducing false positive and false negative outcomes commonly associated with generic alerts and alerts with poor coverage, respectively.

The TTC (Threshold of Toxicological Concern; set at 1.5 μg/day for pharmaceuticals) defines an acceptable patient intake for any unstudied chemical posing a negligible risk of carcinogenicity or other toxic effects. A group of high potency mutagenic carcinogens, defined solely by the presence of particular structural alerts, are referred to as the "cohort of concern" (CoC); aflatoxin-like-, N-nitroso-, and alkyl-azoxy compounds are considered to pose a significant carcinogenic risk at intakes below the TTC. Kroes et al. (2004) derived values for the TTC and CoC in the context of food components, employing a non-transparent dataset never placed in the public domain. Using a reconstructed all-carcinogen dataset from relevant publications, it is now clear that there are exceptions for all three CoC structural classes. N-Nitrosamines represent 62% of the N-nitroso class in the reconstructed dataset. Employing a contemporary dataset, 20% are negative in rodent carcinogenicity bioassays with less than 50% of all N-nitrosamines estimated to fall into the highest risk category. It is recommended that CoC nitrosamines are identified by compound-specific data rather than structural alerts. Thus, it should be possible to distinguish CoC from non-CoC N-nitrosamines in the context of mutagenic impurities described in ICH M7 (R1)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Mycotoxins and their metabolites are a family of compounds that contains a great diversity of both structure and biological properties. Information on their toxicity is spread within several databases and in scientific literature. Due to the number of molecules and their structure diversity, the cost and time required for hazard evaluation of each compound is unrealistic. In that purpose, new approach methodologies (NAMs) can be applied to evaluate such large set of molecules. Among them, quantitative structure-activity relationship (QSAR) in silico models could be useful to predict the mutagenic and carcinogenic properties of mycotoxins. First, a complete list of 904 mycotoxins and metabolites was built. Then, some known mycotoxins were used to determine the best QSAR tools for mutagenicity and carcinogenicity predictions. The best tool was further applied to the whole list of 904 mycotoxins. At the end, 95 mycotoxins were identified as both mutagen and carcinogen and should be prioritized for further evaluation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Toxic plant-produced chemicals, so-called phytotoxins, constitute a category of natural compounds belonging to a diversity of chemical classes. Some of them (e.g., alkaloids, terpenes, saponins) are associated with high toxic potency, while for many of others no toxicological data is available. In this study, the mutagenic potential of 1586 phytotoxins, as obtained from a publicly available database, was investigated applying different in silico approaches. (Q)SAR models (including statistical-based and rule-based systems) were used for the prediction of bacterial in vitro mutagenicity (Ames test) and the results from multiple tools were combined to assign consensus predicted values (i.e., positive, negative, inconclusive). The overall consensus outcome was then employed to investigate relationships between structural features of classes of phytotoxins and potential mutagenicity, allowing the identification of structural alerts raising a specific concern. The results highlighted that about 10% of the screened compounds were predicted to have mutagenic potential and the critical classes of concern, such as alkaloids, were further investigated in terms of subclasses (e.g., indole alkaloids, isoquinoline alkaloids), getting a deeper insight into the mutagenic potential of possible naturally occurring chemicals in plant materials and their structural alerts., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The study was funded by Nestlé., (Copyright © 2022. Published by Elsevier Ltd.)

Maximum common substructures (MCS) have received a lot of attention in the chemoinformatics community. They are typically used as a similarity measure between molecules, showing high predictive performance when used in classification tasks, while being easily explainable substructures. In the present work, we applied the Pairwise Maximum Common Subgraph Feature Generation (PMCSFG) algorithm to automatically detect toxicophores (structural alerts) and to compute fingerprints based on MCS. We present a comparison between our MCS-based fingerprints and 12 well-known chemical fingerprints when used as features in machine learning models. We provide an experimental evaluation and discuss the usefulness of the different methods on mutagenicity data. The features generated by the MCS method have a state-of-the-art performance when predicting mutagenicity, while they are more interpretable than the traditional chemical fingerprints., (© 2023 Wiley-VCH GmbH.)

Even though modeling is considered a valid alternative to mutagenicity testing for substances with known structures, it can be applied for mixtures only if all of the single chemical structures are identified. Within the present work, we investigate a new avenue to exploit computational toxicology for mixtures, such as plant-based food ingredients. Indeed, considering that in the absence of toxicological information, an important early consideration is whether any substance may be genotoxic through the mutagenic mechanism of action, we tried to establish a correspondence between genotoxic structural alerts (SAs) and so-called signature fragment alerts (SFAs). Once this correspondence is established, chromatograms could be screened for chemical features associated with genotoxic alerts. Pyrrolizidine alkaloids (PAs), a large group of natural toxins (several of them known as genotoxic) were used as a case study because their early identification would bring significant benefits. The method was built using 56 PA pure standards, resulting in the characterization of signature fragment alerts. Finally, the approach was verified in real plant-based samples such as herbal tea and alfalfa, where the screening of signature fragment alerts allowed highlighting quickly the presence of genotoxic PAs in plant-based mixtures. Therefore, the SFA analysis can be used for risk prioritization of newly identified PAs and for their identification in mixtures, contributing to the unnecessary use of animal experimentation for genotoxicity testing.

Purpose: Occupational exposure to antineoplastic drugs in hospital settings is recognized to be hazardous, and as such environmental decontamination including degradation and inactivation of such drugs is recommended. To data, although various agents such as oxidants have been reported to be useful for decontamination, simpler, safer, and more convenient methods are required. In this study, the degradation and inactivation efficacy of ozone water, which has newly been introduced for decontamination of antineoplastic drugs in spills, was investigated for formulations of gemcitabine, irinotecan, and paclitaxel., Methods: Antineoplastic formulations (medicinal ingredient: ∼1.5 μmol) were mixed with 50 mL of ozone water (>4 mg/L). The reactions were monitored by high-performance liquid chromatography, and the degradation mixtures were analyzed by 1 H nuclear magnetic resonance spectroscopy in order to obtain the structural information of the degradation products. The formulations of gemcitabine and irinotecan and those degradation mixtures were evaluated for their mutagenicity using the Ames test and cytotoxicity against human cancer cells., Results: gemcitabine and irinotecan were found to be readily degraded by the ozone treatment, and their active sites were suggested to be degraded. In contrast, paclitaxel was hard to be decomposed, possibly owing to the consumption of ozone by the polyoxyethylene castor oil added as a pharmaceutical additive of the formulation. No significant mutagenic changes of Salmonella typhimurium strains used for the Ames test were observed for the samples within the concentration ranges examined. The ozone treatment showed obvious increases in cell viability for gemcitabine formulation, and mild increases for irinotecan formulation., Conclusions: Ozone water was shown to be effective as a decomposition agent for the antineoplastic drug formulations examined, although the efficacy depends on the chemical structures of the drugs and the pharmaceutical additives. It was also suggested that ozone treatment has a tendency to decrease the toxicity of the antineoplastic drug formulations. As such, further studies are required in order to clarify the effects and application limitations of ozone water.

Assessing a compound's mutagenicity using machine learning is an important activity in the drug discovery and development process. Traditional methods of mutagenicity detection, such as Ames test, are expensive and time and labor intensive. In this context, in silico methods that predict a compound mutagenicity with high accuracy are important. Recently, machine-learning (ML) models are increasingly being proposed to improve the accuracy of mutagenicity prediction. While these models are used in practice, there is further scope to improve the accuracy of these models. We hypothesize that choosing the right features to train the model can further lead to better accuracy. We systematically consider and evaluate a combination of novel structural and molecular features which have the maximal impact on the accuracy of models. We rigorously evaluate these features against multiple classification models (from classical ML models to deep neural network models). The performance of the models was assessed using 5- and 10-fold cross-validation and we show that our approach using the molecule structure, molecular properties, and structural alerts as feature sets successfully outperform the state-of-the-art methods for mutagenicity prediction for the Hansen et al. benchmark dataset with an area under the receiver operating characteristic curve of 0.93. More importantly, our framework shows how combining features could benefit model accuracy improvements., (© The Author(s) 2022. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Oxidative lesions, such as 8-oxo-dG and 8-oxo-dA, are continuously generated from exposure to reactive oxygen species. While 8-oxo-dG has been extensively studied, 8-oxo-dA has not received as much attention until recently. Herein, we report the synthesis of duplex DNAs incorporating dA, 8-oxo-dA, 7-deaza-dA, 8-Br-dA, and 8-Br-7-deaza-dA, which have different substitutions at 7- and 8-position, for the investigation into the implications of N7-hydrogen and C8-keto on the base pairing preference, mutagenic potential and repair of 8-oxo-dA. Base pairing study suggested that the polar N7-hydrogen and C8-keto of 8-oxo-dA, rather than the syn-preference, might be essential for 8-oxo-dA to form a stable base pair with dG. Insertion and extension studies using KF-exo - and human DNA polymerase β indicated that the efficient dGTP insertion opposite 8-oxo-dA and extension past 8-oxo-dA:dG are contingent upon not only the stable base pair with dG, but also the flexibility of the active site in polymerase. The N7-hydrogen in 8-oxo-dA or C7-hydrogen in 7-deaza-dA and 8-Br-7-deaza-dA was suggested to be important for the recognition by hOGG1, although the excision efficiencies of 7-deaza-dA and 8-Br-7-deaza-dA were much lower than 8-oxo-dA. This study provides an insight into the structure-function relationship of 8-oxo-dA by nucleotide analogues., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Environmental mutagens are chemical and physical substances in the environment that has a potential to induce a wide range of mutations and generate multiple physiological, biochemical, and genetic modifications in humans. Most mutagens are having genotoxic effects on the following generation through germ cells. The influence of germinal mutations on health will be determined by their frequency, nature, and the mechanisms that keep a specific mutation in the population. Early prenatal lethal mutations have less public health consequences than genetic illnesses linked with long-term medical and social difficulties. Physical and chemical mutagens are common mutagens found in the environment. These two environmental mutagens have been associated with multiple neurological disorders and carcinogenesis in humans. Thus in this study, we aim to unravel the molecular mechanism of physical mutagens (UV rays, X-rays, gamma rays), chemical mutagens (dimethyl sulfate (DMS), bisphenol A (BPA), polycyclic aromatic hydrocarbons (PAHs), 5-chlorocytosine (5ClC)), and several heavy metals (Ar, Pb, Al, Hg, Cd, Cr) implicated in DNA damage, carcinogenesis, chromosomal abnormalities, and oxidative stress which leads to multiple disorders and impacting human health. Biological tests for mutagen detection are crucial; therefore, we also discuss several approaches (Ames test and Mutatox test) to estimate mutagenic factors in the environment. The potential risks of environmental mutagens impacting humans require a deeper basic knowledge of human genetics as well as ongoing research on humans, animals, and their tissues and fluids., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Pachira aquatica is a species used for medicinal and food purposes and has numerous phytochemicals that may have systemic toxic effects and damage to genetic material. This study aimed to evaluate acute and short-term oral toxicity, as well as genotoxic and clastogenic effects of oil extracted from P. aquatica (PASO) seeds in rats and Drosophila melanogaster . The results obtained with biochemical and hematological analyses did not show significant changes in any evaluated parameters when compared with reference values for the species used in the study. Data from the histopathological analysis corroborated results found in this study. These findings indicate low acute and short-term toxicity following oral PASO exposure in rats under the experimental conditions tested. Tests performed in rats showed that PASO did not present significant genotoxic or clastogenic effects on the cells analyzed with the three doses tested. Treatment with PASO in the offspring of HB crossing, which showed high cytochrome P450 levels, did not exhibit genotoxic activity, as demonstrated by the SMART test. These results suggest that products from the hepatic oil metabolism did not show genotoxicity under the conditions tested. Together, the results indicate that, under the experimental conditions tested, PASO is safe for repeated intake. As PASO exhibited low potential to cause harmful effects on living organisms, our study encourages further research aimed at assessing its pharmacological activity, since it is a widely consumed plant.

This study investigates degradation processes of three antimicrobials in water (norfloxacin, ciprofloxacin, and sulfamethoxazole) by photolysis, focusing on the prediction of toxicity endpoints via in silico quantitative structure-activity relationship (QSAR) of their transformation products (TPs). Photolysis experiments were conducted in distilled water with individual solutions at 10 mg L -1 for each compound. Identification of TPs was performed by means of LC-TOF-MS, employing a method based on retention time, exact mass fragmentation pattern, and peak intensity. Ten main compounds were identified for sulfamethoxazole, fifteen for ciprofloxacin, and fifteen for norfloxacin. Out of 40 identified TPs, 6 have not been reported in the literature. Based on new data found in this work, and TPs already reported in the literature, we have proposed degradation pathways for all three antimicrobials, providing reasoning for the identified TPs. QSAR risk assessment was carried out for 74 structures of possible isomers. QSAR predictions showed that all 19 possible structures of sulfamethoxazole TPs are non-mutagenic, whereas 16 are toxicant, 18 carcinogenic, and 14 non-readily biodegradable. For ciprofloxacin, 28 out of the 30 possible structures for the TPs are mutagenic and non-readily biodegradable, and all structures are toxicant and carcinogenic. All 25 possible norfloxacin TPs were predicted mutagenic, toxicant, carcinogenic, and non-readily biodegradable. Results obtained from in silico QSAR models evince the need of performing risk assessment for TPs as well as for the parent antimicrobial. An expert analysis of QSAR predictions using different models and degradation pathways is imperative, for a large variety of structures was found for the TPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

N 6-(2-Deoxy-α,β-d- erythro -pentofuranosyl)-2,6-diamino-4-hydroxy-5-formamido pyrimidine (Fapy•dG) is a prevalent form of genomic DNA damage. Fapy•dG is formed in greater amounts under anoxic conditions than the well-studied, chemically related 7,8-dihydro-8-oxo-2'-deoxyguanosine (8-oxodGuo). Fapy•dG is more mutagenic in mammalian cells than 8-oxodGuo. A distinctive property of Fapy•dG is facile epimerization, but prior works with Fapy•dG analogues have precluded determining its effect on chemistry. We present crystallographic characterization of natural Fapy•dG in duplex DNA and as the template base for DNA polymerase β (Pol β). Fapy•dG adopts the β-anomer when base paired with cytosine but exists as a mixture of α- and β-anomers when promutagenically base paired with adenine. Rotation about the bond between the glycosidic nitrogen atom and the pyrimidine ring is also affected by the opposing nucleotide. Sodium cyanoborohydride soaking experiments trap the ring-opened Fapy•dG, demonstrating that ring opening and epimerization occur in the crystalline state. Ring opening and epimerization are facilitated by propitious water molecules that are observed in the structures. Determination of Fapy•dG mutagenicity in wild type and Pol β knockdown HEK 293T cells indicates that Pol β contributes to G → T transversions but also suppresses G → A transitions. Complementary kinetic studies have determined that Fapy•dG promotes mutagenesis by decreasing the catalytic efficiency of dCMP insertion opposite Fapy•dG, thus reducing polymerase fidelity. Kinetic studies have determined that dCMP incorporation opposite the β-anomer is ∼90 times faster than the α-anomer. This research identifies the importance of anomer dynamics, a feature unique to formamidopyrimidines, when considering the incorporation of nucleotides opposite Fapy•dG and potentially the repair of this structurally unusual lesion.

A series of quaternary diammonium salts derivatives of 1,4:3,6-dianhydro-l-iditol were synthesized, using isommanide (1,4:3,6-dianhydro-d-mannitol) as a starting material. Both aromatic (pyridine, 4-( N , N -dimethylamino)pyridine (DMAP), (3-carboxamide)pyridine; N -methylimidazole) and aliphatic (trimethylamine, N , N -dimethylhexylamine, N , N -dimethyloctylamine, N , N -dimethyldecylamine) amines were used, giving eight gemini quaternary ammonium salts (QAS). All salts were tested for their antimicrobial activity against yeasts, Candida albicans and Candida glabrata , as well as bacterial Staphylococcus aureus and Escherichia coli reference strains. Moreover, antibacterial activity against 20 isolates of S. aureus collected from patients with skin and soft tissue infections ( n = 8) and strains derived from subclinical bovine mastitis milk samples ( n = 12) were evaluated. Two QAS with octyl and decyl residues exhibited antimicrobial activity, whereas those with two decyl residues proved to be the most active against the tested pathogens, with MIC of 16-32, 32, and 8 µg/mL for yeast, E. coli, and S. aureus reference and clinical strains, respectively. Only QAS with decyl residues proved to be cytotoxic in MTT assay against human keratinocytes (HaCaT), IC 50 12.8 ± 1.2 μg/mL. Ames test was used to assess the mutagenic potential of QAS, and none of them showed mutagenic activity in the concentration range 4-2000 µg/plate.

Joint femtosecond fluorescence upconversion experiments and theoretical calculations provide a hitherto unattained degree of characterization and understanding of the mutagenic etheno adduct 3,N4-etheno-2'-deoxycytidine (εdC) excited state relaxation. This endogenously formed lesion is attracting great interest because of its ubiquity in human tissues and its highly mutagenic properties. The εdC fluorescence is modified with respect to that of the canonical base dC, with a 3-fold increased lifetime and quantum yield at neutral pH. This behavior is amplified upon protonation of the etheno ring (εdCH + ). Quantum mechanical calculations show that the lowest energy state ππ*1 is responsible for the fluorescence and that the main nonradiative decay pathway to the ground state goes through an ethene-like conical intersection, involving the out-of-plane motion of the C5 and C6 substituents. This conical intersection is lower in energy than the ππ* state ( ππ*1 ) minimum, but a sizable energy barrier explains the increase of εdC and εdCH + fluorescence lifetimes with respect to that of dC.

Carcinogens such as heterocyclic amine (HCA), produced during meat cooking, pose a risk of digestive and reproductive cancers in humans. Nevertheless, the exact mechanisms for HCA formation in meat and the control of HCA formation are not known. In this review, we provide an overview of the main cause of HCA formation in cooked meat, fundamental data on natural materials to inhibit HCA carcinogenicity, and methods to analyze HCA in cooked meat. Related past studies has shown that natural substances contain various components that act as antioxidants, and these antioxidants can prevent HCA and mutagenic factors. Free radicals and DNA adducts produced by HCA metabolism have carcinogenic properties. Antioxidants have been found to inhibit oxidative stress caused by free radicals and DNA adducts. Therefore, we can be hypothesized that various natural materials can inhibit HCA carcinogens and mutagens., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Due to the link with serious adverse health effects, genotoxicity is an important toxicological endpoint in each regulatory setting with respect to human health, including for pharmaceuticals. To this extent, a compound potential to induce gene mutations as well as chromosome damage needs to be addressed. For chromosome damage, i.e., the induction of structural or numerical chromosome aberrations, several in vitro and in vivo test methods are available. In order to rapidly collect toxicological data without the need for test material, several in silico tools for chromosome damage have been developed over the last years. In this chapter, a battery of freely available in silico chromosome damage prediction tools for chromosome damage is applied on a dataset of pharmaceuticals. Examples of the different outcomes obtained with the in silico battery are provided and briefly discussed. Furthermore, results for coumarin are presented in more detail as a case study. Overall, it can be concluded that although they are in general less developed than those for mutagenicity, in silico tools for chromosome damage can provide valuable information, especially when combined in a battery., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Industrial needs and regulatory requirements have played a significant role in accelerating the use of nontesting methods including in silico tools as alternatives to animal testing. The main interest is not solely on the use of in silico tools, or in read-across, but on better toxicological safety assessment of substances, and for this purpose more advanced, integrated strategies have to be implemented. VEGAHUB wants to promote this broader view, not necessarily focused on a specific approach. Applying multiple tools and complementary approaches instead of one technique may provide more elements for a more robust evaluation, but at the same time it is important to have a conceptual scheme to integrate multiple, heterogeneous lines of evidence. We will show how the user can benefit from the diversity of tools available within the platform VEGAHUB for assessing the biological properties of chemical substances on an example of (non)mutagenicity., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Thermal treatment of protein-rich food can lead to the formation of biologically active heterocyclic aromatic amines (HAAs). One of the methods to learn how to reduce the content as well as the influence of these compounds on heath is the study of factors inhibiting their synthesis. In the current investigation, the effect of onion and garlic on the formation of six possibly carcinogenic non-polar HAAs (α-, γ- and δ-carbolines) and two co-mutagenic β-carbolines (harmane and norharmane) was evaluated by comparing their contents in meat and gravy samples obtained from pan-fried pork dishes prepared in the presence and absence of these vegetables. Carbolines were isolated from food samples by solid phase extraction. The quantitative analysis was performed by high-performance liquid chromatography with fluorescence detection. The concentrations of individual compounds in dishes prepared without added vegetables ranged from 0.02 ng g -1 (3-amino-1,4-dimethyl-5 H-pyrido(4,3-b)indole; Trp- P -1) to 10.1 ng g -1 of meat (2-amino-9 H-pyrido[2,3-b]indole; AαC). Onion (30 g/100 g of meat) and garlic (15 g/100 g of meat) lowered the total content (in meat and gravy) of the α-, δ- and γ-carbolines in the range from 52% to 87%. In contrast, onion caused an increase in the norharmane concentration both in meat and gravy. The percentage of carbolines in the gravies (assuming that their total content in meat and gravy is 100%) was higher in dishes prepared with onion and garlic than in dishes without these seasonings.

Genotoxicity testing plays an important role in the safety assessment of pharmaceuticals, pesticides and chemical substances. Among the guidelines for various genotoxicity tests, the in vitro genotoxicity test battery comprises the bacterial Ames test and mammalian cell assays. Several chemicals exhibit conflicting results for the bacterial Ames test and mammalian cell genotoxicity studies, which may stem from the differences in DNA repair capacity or metabolism, between different cell types or species. For better understanding the mechanistic implications regarding conflict outcomes between different assay systems, it is necessary to develop in vitro genotoxicity testing approaches with higher specificity towards DNA-damaging reagents. We have recently established an improved thymidine kinase (TK) gene mutation assay (TK assay) i.e. deficient in DNA excision repair system using human lymphoblastoid TK6 cells lacking XRCC1 and XPA (XRCC1-/-/XPA-/-), the core factors of base excision repair (BER) and nucleotide excision repair (NER), respectively. This DNA repair-deficient TK6 cell line is expected to specifically evaluate the genotoxic potential of chemical substances based on the DNA damage. We focussed on four reagents, N-(1-naphthyl)ethylenediamine dihydrochloride (NEDA), p-phenylenediamine (PPD), auramine and malachite green (MG) as the Ames test-positive chemicals. In our assay, assessment using XRCC1-/-/XPA-/- cells revealed no statistically significant increase in the mutant frequencies after treatment with NEDA, PPD and MG, suggesting the chemicals to be non-genotoxic in humans. The observations were consistent with that of the follow-up in vivo studies. In contrast, the mutant frequency was markedly increased in XRCC1-/-/XPA-/- cells after treatment with auramine. The results suggest that auramine is the genotoxic reagent that preferentially induces DNA damages resolved by BER and/or NER in mammals. Taken together, BER/NER-deficient cell-based genotoxicity testing will contribute to elucidate the mechanism of genotoxicity and therefore play a pivotal role in the accurate safety assessment of chemical substances., (© The Author(s) 2021. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society.All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The current article aimed to evaluate the in vitro mutagenicity of ten fried meat-based food extracts obtained from different catering companies from Navarra (Spain). A miniaturized 6-well version of the Ames test in Salmonella typhimurium TA98, and the in vitro micronucleus test (OECD TG 487) in TK6 cells were performed. None of the ten extracts of fried meat-based food induced gene mutations in S. typhimurium TA98 with or without metabolic activation, but five induced chromosomal aberrations after 24 h treatment of TK6 without metabolic activation. More studies are needed to check the biological relevance of these in vitro studies., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Previous reports demonstrated that aristolochic acids (AAs) exposure-induced nephrotoxicity, mutations, and tumorigenesis are mainly due to aristolochic acid I (AAI). Notably, the chemical structure of aristolochic acid IVa (AAIVa), which exists at higher levels in many Aristolochiaceae herbs, is extremely similar to AAI. In lack of toxicological data, it is unknown whether AAIVa exposure leads to aristolochic acid nephropathy (AAN), mutations, and tumorigenesis as of AAI. To answer these questions, mice were administered AAIVa by single or repeated long-term gavage, while AAI was used as a positive control. We found that single gavage of 40 mg/kg of AAIVa exhibited no obvious toxicity. Also, there were no tumors or death in mice administrated with 1 and 10 mg/kg of AAIVa for 6 months followed by a 12-month recovery time. There were no noteworthy alterations in gene mutation frequency in the kidney, liver, and stomach between the AAIVa and control mice. Fascinatingly, AA-associated mutational signatures, adenine-to-thymine (A>T) transversions, were absent in AAIVa-treated mice. Nonetheless, 10 mg/kg of AAIVa triggered lymphocytic infiltration and slight fibrous hyperplasia in the kidney at the 6 th month; however, these were alleviated at the 12 th and 18 th months. On the contrary, AAI (positive control) caused severe diffuse fibrosis, tubular atrophy, necrosis, tumors in the forestomach and kidney, and death after the 6 th month. It seems that long-term AAIVa exposure induced mild renal lesions could be due to the activation of the canonical or noncanonical transforming growth factor-β (TGFβ) pathway. Overall, these findings suggest that the mutagenicity and carcinogenic risk of AAIVa are very low., (Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Potentially, the toxicity of multiwalled carbon nanotubes (MWCNTs) can be reduced in a safe-by-design strategy. We investigated if genotoxicity and pulmonary inflammation of MWCNTs from the same batch were lowered by a) reducing length and b) introducing COOH-groups into the structure. Mice were administered: 1) long and pristine MWCNT (CNT-long) (3.9 μm); 2) short and pristine CNT (CNT-short) (1 μm); 3) CNT modified with high ratio COOH-groups (CNT-COOH-high); 4) CNT modified with low ratio COOH-groups (CNT-COOH-low). MWCNTs were dosed by intratracheal instillation at 18 or 54 μg/mouse (∼0.9 and 2.7 mg/kg bw). Neutrophils numbers were highest after CNT-long exposure, and both shortening the MWCNT and addition of COOH-groups lowered pulmonary inflammation (day 1 and 28). Likewise, CNT-long induced genotoxicity, which was absent with CNT-short and after introduction of COOH groups. In conclusion, genotoxicity and pulmonary inflammation of MWCNTs were lowered, but not eliminated, by shortening the fibres or introducing COOH-groups., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The ICH M7 (R1) guideline recommends the use of complementary (Q)SAR models to assess the mutagenic potential of drug impurities as a state-of-the-art, high-throughput alternative to empirical testing. Additionally, it includes a provision for the application of expert knowledge to increase prediction confidence and resolve conflicting calls. Expert knowledge, which considers structural analogs and mechanisms of activity, has been valuable when models return an indeterminate (equivocal) result or no prediction (out-of-domain). A retrospective analysis of 1002 impurities evaluated in drug regulatory applications between April 2017 and March 2019 assessed the impact of expert review on (Q)SAR predictions. Expert knowledge overturned the default predictions for 26% of the impurities and resolved 91% of equivocal predictions and 75% of out-of-domain calls. Of the 261 overturned default predictions, 15% were upgraded to equivocal or positive and 79% were downgraded to equivocal or negative. Chemical classes with the most overturns were primary aromatic amines (46%), aldehydes (45%), Michael-reactive acceptors (37%), and non-primary alkyl halides (33%). Additionally, low confidence predictions were the most often overturned. Collectively, the results suggest that expert knowledge continues to play an important role in an ICH M7 (Q)SAR prediction workflow and triaging predictions based on chemical class and probability can improve (Q)SAR review efficiency., (Copyright © 2021. Published by Elsevier Inc.)

Deep neural networks are effective in learning directly from low-level encoded data without the need of feature extraction. This paper shows how QSAR models can be constructed from 2D molecular graphs without computing chemical descriptors. Two graph convolutional neural network-based models are presented with and without a Bayesian estimation of the prediction uncertainty. The property under investigation is mutagenicity: Models developed here predict the output of the Ames test. These models take the SMILES representation of the molecules as input to produce molecular graphs in terms of adjacency matrices and subsequently use attention mechanisms to weight the role of their subgraphs in producing the output. The results positively compare with current state-of-the-art models. Furthermore, our proposed model interpretation can be enhanced by the automatic extraction of the substructures most important in driving the prediction, as well as by uncertainty estimations., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The potential risks of environmental nanoparticles (NPs), in particular Polystyrene Nanoparticles (PNPs), is an emerging problem; specifically, the interaction of PNPs with intestinal cells has not been characterized so far. The mechanism by which polystyrene particles are transferred to humans has not yet been clarified, whether directly through ingestion from contaminated food. We evaluated the interaction between PNPs and colorectal adenocarcinoma cells (HCT116). Cells were exposed to different concentrations of PNPs, metabolic activity and the consequent cytotoxic potential were assessed through viability test; we evaluated the PNP genotoxic potential through the Cytokinesis-Block Micronucleus cytome (CBMN cyt) assay. Finally, we detected Reactive Oxygen Species (ROS) production after NPs exposure and performed Western Blot analysis to analyze the enzymes (SOD1, SOD2, Catalase, Glutathione Peroxidase) involved in the cell detoxification process that comes into play during the cell-PNPs interaction. This work analyzes the cyto and genotoxicity of PNPs in the colorectal HCT116 cell line, in particular the potential damage from oxidative stress produced by PNPs inside the cells related to the consequent nuclear damage. Our results show moderate toxicity of PNPs both in terms of ROS production and DNA damage. Further studies will be needed on different cell lines to have a more complete picture of the impact of environmental pollution on human health in terms of PNPs cytotoxicity and genotoxicity., Competing Interests: The authors have declared that no competing interests exist.

We report here the synthesis, crystal structure, characterization and anticancer activity of a copper(ii)-hydrazone complex, [Cu(MeBHoVa)(H2O)2](NO3) (for short, CuHL), against human breast cancer cells on monolayer (2D) and spheroids/mammospheres (3D). The solid-state molecular structure of the complex has been determined by X-ray diffraction methods. The conformational space was searched and geometries were optimized both in the gas phase and including solvent effects by computational methods based on DFT. The compound has been characterized in the solid state and in solution by spectroscopic (FTIR, Raman, UV-vis) methods. The results were compared with those obtained for the hydrazone ligand and complemented with DFT calculations. Cell viability assays on MCF7 (IC50(CuHL) = 1.7 ± 0.1 μM, IC50(CDDP) = 42.0 ± 3.2 μM) and MDA-MB-231 (IC50(CuHL) = 1.6 ± 0.1 μM, IC50(CDDP) = 131.0 ± 18 μM) demonstrated that the complex displays higher antitumor activity than cisplatin (CDDP) on 2D and 3D human breast cancer cell models. Molecular docking and molecular dynamics simulations showed that CuHL could interacts with DNA, inducing a significant genotoxic effect on both breast cancer cells from 0.5 to 1 μM. On the other hand, CuHL increases the ROS production and induces cell programmed death on breast cancer cells at very low micromolar concentrations (0.5-1.0 μM). Moreover, the compound decreased the amount of breast CSCs on MCF7 and MDA-MB-231 cells reducing the percentage of CD44+/CD24-/low cells from 0.5 to 1.5 μM. In addition, CuHL overcame CDDP with an IC50 value 65-fold lower against breast multicellular spheroids ((IC50(CuHL) = 2.2 ± 0.3 μM, IC50(CDDP) = 125 ± 4.5 μM)). Finally, CuHL reduced mammosphere formation capacity, hence affecting the size and number of mammospheres and showing that the complex exhibits antitumor properties on monolayer (2D) and spheroids (3D) derived from human breast cancer cells.

Lignin is a complex phenolic biopolymer present in plant cell walls and a by-product of the cellulose pulping industry. Lignin has functional properties, such as antioxidant activity, that make it a potential natural active ingredient for health-care products. However, not all safety aspects of lignin fractions have been adequately investigated. Herein, we evaluated the antioxidant and genotoxic potential of two hardwood kraft lignins (F3 and F5). The chemical characterization of F3 and F5 demonstrated their thermal stability and the presence of different phenolic units, while the DPPH assay confirmed the antioxidant activity of these lignin fractions. Despite being antioxidants in the DPPH assay, F3 and F5 were capable of generating intracellular reactive oxygen species (ROS) and subsequently causing oxidative DNA damage (Comet assay) in HepG2 cells. The biological relevance of the DPPH assay might be uncertain in some cases; therefore, we suggest combining in chemico tests with biological system-based tests to determine efficacy and safety levels of lignins and define appropriate applications of lignins for consumer products. Moreover, kraft lignins obtained by acid precipitation may pose risks to human health; however, as genotoxicity is not the sole endpoint of toxicity required in hazard assessments, additional toxicological evaluations are needed., (Copyright © 2021 Elsevier B.V. All rights reserved.)