Mutagenic potential and structural alerts of phytotoxins. (March 2023)

• Record Type: Journal Article
• Authors: Bassan, Arianna; Pavan, Manuela; Lo Piparo, Elena
• Is Part Of: Food and chemical toxicology. Volume 173(2023)
• Publication Date: 2023-03
• Subjects: In silico -- QSAR -- Bacterial mutagenicity -- Phytotoxins -- Expert systems -- Alerts; 2D two-dimensional -- 3D three-dimensional -- ADI Applicability Domain Index -- IndVal Indicator Value -- NAM New Approach Methodology -- PSM Plant Secondary Metabolite -- (Q)SAR (Q)uantitative Structure Activity Relationship -- SA Structural Alert -- SDF Structure Data File -- SMILES Simplified Molecular Input Line Entry System -- TPPT Toxic Plant-Phytotoxin; Toxicology -- Periodicals; Food poisoning -- Periodicals; Food Poisoning -- Periodicals; Toxicology -- Periodicals; Toxicologie -- Périodiques; Intoxications alimentaires -- Périodiques; Food poisoning; Toxicology; Periodicals; Electronic journals; 615.9
• DOI: 10.1016/j.fct.2022.113562
• Languages: English
• ISSNs: 0278-6915

Abstract

Abstract: 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. Graphical abstract: Image 1 Highlights: (Q)SARs were used to investigate potential mutagenicity of phytotoxins. Phytotoxin classes were associated with structural alerts for potential mutagenicity. The identified structural alerts could be helpful in supporting read-across and grouping. This analysis aims at supporting prioritization of natural compounds of concern.