In Silico Prediction of Chemically Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results

Mombelli, Enrico; Raitano, Giuseppa; Benfenati, Emilio

doi:10.1007/978-1-4939-3609-0_5

Cited by 12 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a study, (Mombelli et al, 2016) used three models included in the VEGA system (Caesar, SARpy, and ToxTree as implemented in VEGA) to study differences in performance between retro-fitting application, and application only to chemicals simultaneously outside the training set and inside a rigorously defined Applicability Domain ( Figure 6).…”

Section: Influence Of the Applicability Domain And Of Training / Tesmentioning

confidence: 99%

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Benigni¹,

Battistelli²,

Bossa³

et al. 2019

EFS3

View full text Add to dashboard Cite

To facilitate the practical implementation of the guidance on the residue definition for dietary risk assessment, EFSA has organized an evaluation of applicability of existing in silico models for predicting the genotoxicity of pesticides and their metabolites, including analysis of the impact on genotoxicity of the metabolic structural changes. The prediction ability of (Q)SARs for in vitro and in vivo tests were evaluated. For the Ames test, all (Q)SAR models generated statistically significant predictions, comparable with the experimental variability of the test; instead, the reliability of the (Q)SAR models for assays / endpoints different from in vitro bacterial mutagenicity appears to be quite far from optimality. Secondly, two new Read Across approaches were applied to predict Ames mutagenicity and in vitro Chromosomal Aberrations: Read Across was largely successful for predicting the Ames test results, but much less for in vitro Chromosomal Aberrations. The worse results for endpoints different from Ames may be attributable to the several revisions of experimental protocols and evaluation criteria of results that have made the databases qualitatively non‐homogeneous, and poorly suitable for modelling. A third dimension of this research is the evaluation of the impact of the structural changes‐in result of metabolic or degradation processes‐on the genotoxic potential of the substances. Parent/Metabolite structural differences (beyond the known Structural Alerts) that may, or may not cause changes in the Ames mutagenicity were identified and catalogued. In addition, Structural Alerts analysis applied under human expert supervision permitted the rationalization of the large majority of the changes of patterns of genotoxicity. The findings from this work are suitable for being integrated into Weight‐of‐Evidence and Tiered evaluation schemes. The importance of the human expert knowledge is particularly emphasized.

show abstract

Section: Influence Of the Applicability Domain And Of Training / Tesmentioning

confidence: 99%

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Benigni¹,

Battistelli²,

Bossa³

et al. 2019

EFS3

View full text Add to dashboard Cite

show abstract

“…The study of the toxicity of compounds is an important feature in the selection of a drug molecule. In this study, the toxicity of isoquinoline alkaloids (Hepatotoxicity, Mutagenicity, Carcinogenicity, Cytotoxicity, and Immunotoxicity) and their toxicity class were predicted by the ProTox-II server (tox.charite.de/protox_II/) (Banerjee et al 2018 ) and Toxtree 2.5.4 tool (Mombelli et al 2016 ), respectively.…”

Section: Methodsmentioning

confidence: 99%

Inhibitory effects of selected isoquinoline alkaloids against main protease (Mpro) of SARS-CoV-2, in silico study

Sadeghi

Miroliaei

2022

In Silico Pharmacol.

View full text Add to dashboard Cite

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite the production of various vaccines and different treatments, finding natural compounds to control COVID-19 is still a challenging task. Isoquinoline alkaloids are naturally occurring compounds known to have some potential antiviral activity. In this study, ten abundant isoquinoline alkaloids with antiviral activity were selected to analyze the preventive effect on COVID-19. A scrutinized evaluation based on Lipinski’s rule showed that one out of ten compounds was toxic. Based on molecular docking analysis using Autodock software one of the best molecules with maximum negative binding energy was selected for further analysis. The Gromacs simulation analysis revealed that Coptisine has more action against active site M pro of COVID-19. Overall, to make a rational design of various preventive analogues that inhibit the COVID-19, associated in vitro and in vivo analyses are needed to confirm this claim.

show abstract

“…Evidence may come from read across from structurally similar chemicals, use of structural alerts or (Q)SAR models. Modelling of genotoxicity is one of the most extensively developed fields in computational toxicology (Serafimova et al, 2010;Worth et al, 2010Worth et al, , 2013Mombelli et al, 2016;Patlewicz and Fitzpatrick, 2016). This has been facilitated by our understanding of the underlying biological mechanisms, well established experimental protocols, and availability of a large amount of experimental data in the public domain.…”

Section: Genotoxicity Prediction Toolsmentioning

confidence: 99%

Guidance on the use of the Threshold of Toxicological Concern approach in food safety assessment

More¹,

Bampidis²,

Benford³

et al. 2019

EFS2

177

139

View full text Add to dashboard Cite

The Scientific Committee confirms that the Threshold of Toxicological Concern (TTC) is a pragmatic screening and prioritisation tool for use in food safety assessment. This Guidance provides clear step-bystep instructions for use of the TTC approach. The inclusion and exclusion criteria are defined and the use of the TTC decision tree is explained. The approach can be used when the chemical structure of the substance is known, there are limited chemical-specific toxicity data and the exposure can be estimated. The TTC approach should not be used for substances for which EU food/feed legislation requires the submission of toxicity data or when sufficient data are available for a risk assessment or if the substance under consideration falls into one of the exclusion categories. For substances that have the potential to be DNA-reactive mutagens and/or carcinogens based on the weight of evidence, the relevant TTC value is 0.0025 lg/kg body weight (bw) per day. For organophosphates or carbamates, the relevant TTC value is 0.3 lg/kg bw per day. All other substances are grouped according to the Cramer classification. The TTC values for Cramer Classes I, II and III are 30 lg/kg bw per day, 9 lg/kg bw per day and 1.5 lg/kg bw per day, respectively. For substances with exposures below the TTC values, the probability that they would cause adverse health effects is low. If the estimated exposure to a substance is higher than the relevant TTC value, a non-TTC approach is required to reach a conclusion on potential adverse health effects.

show abstract

In Silico Prediction of Chemically Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results

Cited by 12 publications

References 16 publications

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Evaluation of the applicability of existing (Q)SAR models for predicting the genotoxicity of pesticides and similarity analysis related with genotoxicity of pesticides for facilitating of grouping and read across

Inhibitory effects of selected isoquinoline alkaloids against main protease (Mpro) of SARS-CoV-2, in silico study

Guidance on the use of the Threshold of Toxicological Concern approach in food safety assessment

Contact Info

Product

Resources

About