In silico assessment of chemical mutagenesis in comparison with results of Salmonella microsome assay on 909 chemicals

An Emerging Role for Sigma-1 Receptors in the Treatment of Developmental and Epileptic Encephalopathies

Developmental and epileptic encephalopathies (DEEs) are complex conditions characterized primarily by seizures associated with neurodevelopmental and motor deficits. Recent evidence supports sigma-1 receptor modulation in both neuroprotection and antiseizure activity, suggesting that sigma-1 receptors may play a role in the pathogenesis of DEEs, and that targeting this receptor has the potential to positively impact both seizures and non-seizure outcomes in these disorders. Recent studies have demonstrated that the antiseizure medication fenfluramine, a serotonin-releasing drug that also acts as a positive modulator of sigma-1 receptors, reduces seizures and improves everyday executive functions (behavior, emotions, cognition) in patients with Dravet syndrome and Lennox-Gastaut syndrome. Here, we review the evidence for sigma-1 activity in reducing seizure frequency and promoting neuroprotection in the context of DEE pathophysiology and clinical presentation, using fenfluramine as a case example. Challenges and opportunities for future research include developing appropriate models for evaluating sigma-1 receptors in these syndromic epileptic conditions with multisystem involvement and complex clinical presentation.

Virulence genes identification and characterization revealed the presence of the Yersinia High Pathogenicity Island (HPI) in Salmonella from Brazil

Salmonella spp. is one of the major agents of foodborne disease worldwide, and its virulence genes are responsible for the main pathogenic mechanisms of this micro-organism. The whole-genome sequencing (WGS) of pathogens has become a lower-cost and more accessible genotyping tool providing many gene analysis possibilities. This study provided an in silico investigation of 129 virulence genes, including plasmidial and bacteriophage genes from Brazilian strains' public Salmonella genomes. The frequency analysis of the four most sequenced serovars and a temporal analysis over the past four decades was also performed. The NCBI sequence reads archive (SRA) database comprised 1077 Salmonella public whole-genome sequences of strains isolated in Brazil between 1968 and 2018. Among the 1077 genomes, 775 passed in Salmonella in silico Typing (SISTR) quality control, which also identified 41 different serovars in which the four most prevalent were S. Enteritidis, S. Typhimurium, S. Dublin, and S. Heidelberg. Among these, S. Heidelberg presented the most distinct virulence profile, besides presenting Yersinia High Pathogenicity Island (HPI), rare and first reported in Salmonella from Brazil. The genes mgtC, csgC, ssaI and ssaS were the most prevalent within the 775 genomes with more than 99% prevalence. On the other hand, the less frequent genes were astA, iucBCD, tptC and shdA, with less than 1% frequency. All of the plasmids and bacteriophages virulence genes presented a decreasing trend between the 2000 s and 2010 s decades, except for the phage gene grvA, which increased in this period. This study provides insights into Salmonella virulence genes distribution in Brazil using freely available bioinformatics tools. This approach could guide in vivo and in vitro studies besides being an interesting method for the investigation and surveillance of Salmonella virulence. Moreover, here we propose the genes mgtC, csgC, ssaI and ssaS as additional targets for PCR identification of Salmonella in Brazil due to their very high frequency in the studied genomes.

New in silico models to predict in vitro micronucleus induction as marker of genotoxicity

The evaluation of genotoxicity is a fundamental part of the safety assessment of chemicals due to the relevance of the potential health effects of genotoxicants. Among the testing methods available, the in vitro micronucleus assay with mammalian cells is one of the most used and required by regulations targeting several industrial sectors such as the cosmetic industry and food-related sectors. As an alternative to the testing methods, in recent years, lots in silico methods were developed to predict the genotoxicity of chemicals, including models for the Ames mutagenicity test, the in vitro chromosomal aberrations and the in vivo micronucleus assay. We developed several in silico models for the prediction of genotoxicity as reflected by the in vitro micronucleus assay. The resulting models include both statistical and knowledge-based models. The most promising model is the one based on fragments extracted with the SARpy platform. More than 100 structural alerts were extracted, including also fragments associated with the non-genotoxic activity. The model is characterized by high accuracy and the lowest false negative rate, making this tool suitable for chemical screening according to the regulators' needs. The SARpy model will be implemented on the VEGA platform (https://www.vegahub.eu) and will be freely available.

Improvement of quantitative structure-activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project

The International Conference on Harmonization (ICH) M7 guideline allows the use of in silico approaches for predicting Ames mutagenicity for the initial assessment of impurities in pharmaceuticals. This is the first international guideline that addresses the use of quantitative structure–activity relationship (QSAR) models in lieu of actual toxicological studies for human health assessment. Therefore, QSAR models for Ames mutagenicity now require higher predictive power for identifying mutagenic chemicals. To increase the predictive power of QSAR models, larger experimental datasets from reliable sources are required. The Division of Genetics and Mutagenesis, National Institute of Health Sciences (DGM/NIHS) of Japan recently established a unique proprietary Ames mutagenicity database containing 12140 new chemicals that have not been previously used for developing QSAR models. The DGM/NIHS provided this Ames database to QSAR vendors to validate and improve their QSAR tools. The Ames/QSAR International Challenge Project was initiated in 2014 with 12 QSAR vendors testing 17 QSAR tools against these compounds in three phases. We now present the final results. All tools were considerably improved by participation in this project. Most tools achieved >50% sensitivity (positive prediction among all Ames positives) and predictive power (accuracy) was as high as 80%, almost equivalent to the inter-laboratory reproducibility of Ames tests. To further increase the predictive power of QSAR tools, accumulation of additional Ames test data is required as well as re-evaluation of some previous Ames test results. Indeed, some Ames-positive or Ames-negative chemicals may have previously been incorrectly classified because of methodological weakness, resulting in false-positive or false-negative predictions by QSAR tools. These incorrect data hamper prediction and are a source of noise in the development of QSAR models. It is thus essential to establish a large benchmark database consisting only of well-validated Ames test results to build more accurate QSAR models.

In silico prediction of chromosome damage: comparison of three (Q)SAR models

Two major endpoints for genotoxicity tests are gene mutation and chromosome damage (CD), which includes clastogenicity and aneugenicity detected by chromosomal aberration (CA) test or micronucleus (MN) test. Many in silico prediction systems for bacterial mutagenicity (i.e. Ames test results) have been developed and marketed. They show good performance for prediction of Ames mutagenicity. On the other hand, it seems that in silico prediction of CD does not progress as much as Ames prediction. Reasons for this include different mechanisms and detection methods, many false positives and conflicting test results. However, some (quantitative) structure-activity relationship ((Q)SAR) models (e.g. Derek Nexus [Derek], ADMEWorks [AWorks] and CASE Ultra [MCase]) can predict CA test results. Therefore, performances of the three (Q)SAR models were compared using the expanded Carcinogenicity Genotoxicity eXperience (CGX) dataset for understanding current situations and future development. The constructed dataset contained 440 chemicals (325 carcinogens and 115 non-carcinogens). Sensitivity, specificity, accuracy or applicability of each model were 56.0, 86.9, 68.6 or 89.1% in Derek, 67.7, 61.5, 65.2 or 99.3% in AWorks, and 91.0, 64.9, 80.5 or 97.7% in MCase, respectively. The performances (sensitivity and accuracy) of MCase were higher than those of Derek or AWorks. Analysis of predictivity of (Q)SAR models of certain chemical classes revealed no remarkable differences among the models. The tendency of positive prediction by (Q)SAR models was observed in alkylating agents, aromatic amines or amides, aromatic nitro compounds, epoxides, halides and N-nitro or N-nitroso compounds. In an additional investigation, high sensitivity but low specificity was noted in in vivo MN prediction by MCase. Refinement of test data to be used for in silico system (e.g. consideration of cytotoxicity or re-evaluation of conflicting test results) will be needed to improve performance of CD prediction.

Ecotoxicity and genotoxicity of cadmium in different marine trophic levels

Cadmium ecotoxicity and genotoxicity was assessed in three representative species of different trophic levels of marine ecosystems - the calanoid copepod Acartia tonsa, the decapod shrimp, Palaemon varians and the pleuronectiform fish Solea senegalensis. Ecotoxicity endpoints assessed in this study were adult survival, hatching success and larval development ratio (LDR) for A. tonsa, survival of the first larval stage (zoea I) and post-larvae of P. varians, egg and larvae survival, as well as the presence of malformations in the larval stage of S. senegalensis. In vivo genotoxicity was assessed on adult A. tonsa, the larval and postlarval stage of P. varians and newly hatched larvae of S. senegalensis using the comet assay. Results showed that the highest sensitivity to cadmium is displayed by A. tonsa, with the most sensitive endpoint being the LDR of nauplii to copepodites. Sole eggs displayed the highest tolerance to cadmium compared to the other endpoints evaluated for all tested species. Recorded cadmium toxicity was (by increasing order): S. senegalensis eggs < P. varians post-larvae < P. varians zoea I < S. senegalensis larvae < A. tonsa eggs < A. tonsa LDR. DNA damage to all species exposed to cadmium increased with increasing concentrations. Overall, understanding cadmium chemical speciation is paramount to reliably evaluate the effects of this metal in marine ecosystems. Cadmium is genotoxic to all three species tested and therefore may differentially impact individuals and populations of marine taxa. As A. tonsa was the most sensitive species and occupies a lower trophic level, it is likely that cadmium contamination may trigger bottom-up cascading effects in marine trophic interactions.

Genotoxicity of cadmium chloride in the marine gastropod Nerita chamaeleon using comet assay and alkaline unwinding assay

This paper presents an evaluation of the genotoxic effects of cadmium chloride (CdCl2 ) on marine gastropod, Nerita chamaeleon following the technique of comet assay and the DNA alkaline unwinding assay (DAUA). In this study, the extent of DNA damage in gill cells of N. chamaeleon was measured after in vivo exposure to four different concentrations (10, 25, 50, and 75 µg/L) of CdCl2 . In vitro exposure of hydrogen peroxide (H2 O2 ; 1, 10, 25, and 50 µM) of the gill cells showed a significant increase in the percentage tail DNA, Olive tail moment, and tail length (TL). Significant changes in percentage tail DNA by CdCl2 exposure were observed in all exposed groups of snails with respect to those in control. Exposure to 75 µg/L of CdCl2 produced significant decrease in DNA integrity as measured by DAUA at all duration with respect to control. In vivo exposure to different concentrations of CdCl2 (10, 25, 50, and 75 µg/L) to N. chamaeleon showed considerable increase in DNA damage as observed by both alkaline comet assay and the DAUA. The extent of DNA damage in marine gastropods determined by the application of alkaline comet assay and DAUA clearly indicated the genotoxic responses of marine gastropod, N. chamaeleon to a wide range of cadmium concentration in the marine environment.

Evaluation of QSAR models for the prediction of ames genotoxicity: a retrospective exercise on the chemical substances registered under the EU REACH regulation

We evaluated the performance of seven freely available quantitative structure-activity relationship models predicting Ames genotoxicity thanks to a dataset of chemicals that were registered under the EU Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation. The performance of the models was estimated according to Cooper's statistics and Matthew's Correlation Coefficients (MCC). The Benigni/Bossa rule base originally implemented in Toxtree and re-implemented within the Virtual models for property Evaluation of chemicals within a Global Architecture (VEGA) platform displayed the best performance (accuracy = 92%, sensitivity = 83%, specificity = 93%, MCC = 0.68) indicating that this rule base provides a reliable tool for the identification of genotoxic chemicals. Finally, we elaborated a consensus model that outperformed the accuracy of the individual models.

Role of in silico genotoxicity tools in the regulatory assessment of pharmaceutical impurities

The toxicological assessment of genotoxic impurities is important in the regulatory framework for pharmaceuticals. In this context, the application of promising computational methods (e.g. Quantitative Structure-Activity Relationships (QSARs), Structure-Activity Relationships (SARs) and/or expert systems) for the evaluation of genotoxicity is needed, especially when very limited information on impurities is available. To gain an overview of how computational methods are used internationally in the regulatory assessment of pharmaceutical impurities, the current regulatory documents were reviewed. The software recommended in the guidelines (e.g. MCASE, MC4PC, Derek for Windows) or used practically by various regulatory agencies (e.g. US Food and Drug Administration, US and Danish Environmental Protection Agencies), as well as other existing programs were analysed. Both statistically based and knowledge-based (expert system) tools were analysed. The overall conclusions on the available in silico tools for genotoxicity and carcinogenicity prediction are quite optimistic, and the regulatory application of QSAR methods is constantly growing. For regulatory purposes, it is recommended that predictions of genotoxicity/carcinogenicity should be based on a battery of models, combining high-sensitivity models (low rate of false negatives) with high-specificity ones (low rate of false positives) and in vitro assays in an integrated manner.

Synthesis of 86 species of 1,5-diaryl-3-oxo-1,4-pentadienes analogs of curcumin can yield a good lead in vivo

Background

Curcumin is known to possess many anti-tumor properties such as inhibition of tumor growth and induction of apotosis. However, limited bioavailability of curcumin prevents its clinical application. A synthesized curcumin analog, 1,5-diaryl-3-oxo-1,4-pentadiene such as GO-Y030, has the improved anti-tumor potential in vitro as well as in mouse model of colorectal carcinogenesis.

Results

These compounds were divided into two groups; one is the higher anti-proliferative group, in which 79.7% of 1,5-diaryl-3-oxo-1,4-pentadienes were clustered. One of the 1,5-diaryl-3-oxo-1,4-pentadiene analogs, GO-Y078 has the most enhanced growth inhibition, and its solubility was improved, compared with curcumin. GO-Y078 inhibits NF-κB transactivation, as well as expression of TP53 and DR5 more effectively than curcumin. In a mouse model, GO-Y078 presented 1.4 fold more survival elongation that was not achieved by curcumin and GO-Y030.

Conclusions

The 1,5-diaryl-3-oxo-1,4-pentadiene analogs can yield good lead compounds for cancer chemotherapy, to overcome low bioavailability of curcumin.

A review of the electrophilic reaction chemistry involved in covalent DNA binding

The need to assess the ability of a chemical to act as a mutagen or a genotoxic carcinogen (collectively termed genotoxicity) is one of the primary requirements in regulatory toxicology. Several pieces of legislation have led to an increased interest in the use of in silico methods, specifically the formation of chemical categories for the assessment of toxicological endpoints. A key step in the development of chemical categories for genotoxicity is defining the organic chemistry associated with the formation of a covalent bond between DNA and an exogenous chemical. This organic chemistry is typically defined as structural alerts. To this end, this article has reviewed the literature defining the structural alerts associated with covalent DNA binding. Importantly, this review article also details the mechanistic organic chemistry associated with each of the structural alerts. This information is extremely important in terms of meeting regulatory requirements for the acceptance of the chemical category approach. The structural alerts and associated mechanistic chemistry have been incorporated into the Organisation for Economic Co-operation and Development (OECD) (Q)SAR Application Toolbox.

[In silico, in vitro, in omic experimental models and drug safety evaluation]

Over the last few decades, toxicology has benefited from scientific, technical, and bioinformatic developments relating to patient safety assessment during clinical and drug marketing studies. Based on this knowledge, new in silico, in vitro, and "omic" experimental models are emerging. Although these models cannot currently replace classic safety evaluations performed on laboratory animals, they allow compounds with unacceptable toxicity to be rejected in the early stages of drug development, thereby reducing the number of laboratory animals needed. In addition, because these models are particularly adapted to mechanistic studies, they can help to improve the relevance of the data obtained, thus enabling better prevention and screening of the adverse effects that may occur in humans. Much progress remains to be done, especially in the field of validation. Nevertheless, current efforts by industrial, academic laboratories, and regulatory agencies should, in coming years, significantly improve preclinical drug safety evaluation thanks to the integration of these new methods into the drug research and development process.