Transformation products (TPs) of organic contaminants in aquatic environments are still rarely considered in water quality and chemical risk assessment, although they have been found in concentrations that are of concern. Since many different TPs can potentially be formed in the environment and analytical standards are typically lacking for these compounds, knowledge on the prevalence of TPs in aquatic environments is fragmentary. In this study, an efficient procedure was therefore developed to comprehensively screen for large numbers of potential TPs in environmental samples. It is based on a target list of plausible TPs that has been assembled using the University of Minnesota Pathway Prediction System (UM-PPS) for the computer-aided prediction of products of microbial metabolism and an extensive search for TPs reported in the scientific literature. The analytical procedure for screening of the compounds on the target list has been developed to allow for the detection of a broad range of compounds in co...

Identification of transformation products of organic contaminants in natural waters by computer-aided prediction and high-resolution mass spectrometry.

Effect-directed analysis supporting monitoring of aquatic environments - An in-depth overview

This Guidance describes how to perform hazard identification for endocrine-disrupting properties by following the scientific criteria which are outlined in Commission Delegated Regulation (EU) 2017/2100 and Commission Regulation (EU) 2018/605 for biocidal products and plant protection products, respectively.

Guidance for the identification of endocrine disruptors in the context of Regulations (EU) No 528/2012 and (EC) No 1107/2009

Novel flame retardants: Estimating the physical-chemical properties and environmental fate of 94 halogenated and organophosphate PBDE replacements

BitterDB (http://bitterdb.agri.huji.ac.il) was introduced in 2012 as a central resource for information on bitter-tasting molecules and their receptors. The information in BitterDB is frequently used for choosing suitable ligands for experimental studies, for developing bitterness predictors, for analysis of receptors promiscuity and more. Here, we describe a major upgrade of the database, including significant increase in content as well as new features. BitterDB now holds over 1000 bitter molecules, up from the initial 550. When available, quantitative sensory data on bitterness intensity as well as toxicity information were added. For 270 molecules, at least one associated bitter taste receptor (T2R) is reported. The overall number of ligand-T2R associations is now close to 800. BitterDB was extended to several species: in addition to human, it now holds information on mouse, cat and chicken T2Rs, and the compounds that activate them. BitterDB now provides a unique platform for structure-based studies with high-quality homology models, known ligands, and for the human receptors also data from mutagenesis experiments, information on frequently occurring single nucleotide polymorphisms and links to expression levels in different tissues.

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BitterDB: taste ligands and receptors database in 2019.

The OECD QSAR Toolbox is a software application intended to be used by governments, the chemical industry and other stakeholders in filling gaps in (eco)toxicity data needed for assessing the hazards of chemicals. The development and release of the Toolbox is a cornerstone in the computerization of hazard assessment, providing an 'all inclusive' tool for the application of category approaches, such as read-across and trend analysis, in a single software application, free of charge. The Toolbox incorporates theoretical knowledge, experimental data and computational tools from various sources into a logical workflow. The main steps of this workflow are substance identification, identification of relevant structural characteristics and potential toxic mechanisms of interaction (i.e. profiling), identification of other chemicals that have the same structural characteristics and/or mechanism (i.e. building a category), data collection for the chemicals in the category and use of the existing experimental data to fill the data gap(s). The description of the Toolbox workflow and its main functionalities is the scope of the present article.

QSAR Toolbox - workflow and major functionalities.

The unprecedented pollution of the environment by xenobiotic compounds has provoked the need to understand the biodegradation potential of chemicals. Mechanistic understanding of microbial degradation is a premise for adequate modelling of the environmental fate of chemicals. The aim of the present paper is to describe abiotic and biotic models implemented in CATALOGIC software. A brief overview of the specificities of abiotic and microbial degradation is provided followed by detailed descriptions of models built in our laboratory during the last decade. These are principally new models based on unique mathematical formalism already described in the first paper of this series, which accounts more adequately than currently available approaches the multipathway metabolic logic in prokaryotes. Based on simulated pathways of degradation, the models are able to predict quantities of transformation products, biological oxygen demand (BOD), carbon dioxide (CO(2)) production, and primary and ultimate half-lives. Interpretation of the applicability domain of models is also discussed.

Simulation of chemical metabolism for fate and hazard assessment. II CATALOGIC simulation of abiotic and microbial degradation

The role of metabolism in prioritising chemicals according to their potential adverse health effects is extremely important given the fact that innocuous parents can be transformed into toxic metabolites. Our recent efforts in simulating metabolic activation of chemicals are reviewed in this work. The application of metabolic simulators to predict biodegradation (microbial degradation pathways), bioaccumulation (fish liver metabolism), skin sensitisation (skin metabolism), mutagenicity (rat liver S-9 metabolism) are discussed. The ability of OASIS approach to predict metabolism (toxicokinetics) and toxicity (toxicodynamics) of chemicals resulting from their metabolic activation in a single modelling platform is an important advantage of the method. It allows prioritisation of chemicals due to predicted toxicity of their metabolites.

R Vasilev

Papers

QSAR Toolbox - workflow and major functionalities.

Simulation of chemical metabolism for fate and hazard assessment. II CATALOGIC simulation of abiotic and microbial degradation

Metabolic activation of chemicals: in-silico simulation.