P04-16 in silico applications for the prediction and hazard assessment of transformation products originated from water disinfection treatment processes
“Water from sources used for drinking water production is subjected to a series of disinfection treatment processes to guarantee the inactivation of pathogens and the removal of contaminants from the water, thus assuring safe drinking water to consumers. It is recognized that drinking water sources can be contaminated with traces of anthropogenic substances released into the environment, including plant protection products and biocides. Some of these active substances are expected to undergo transformation reactions to a certain degree during drinking water disinfection processes and form low-level mixtures of transformation products (TPs). As physico-chemical and toxicological characteristics are often unknown, potential risks associated with transformation products are often not well understood. Predictive toxicology can steer risk-based monitoring for TPs in drinking water, supporting the evaluation of potential health risks to safeguard healthy drinking water. Using in silico approaches, it is possible to predict the TPs generated during the reactions involved in disinfection processes for drinking water. A case study of this approach will be presented for S-Metolachlor, a herbicide approved both in the EU and USA. Various open-access computational tools are available to predict TPs formed due to specific reactions associated with water treatment processes. These entail US EPA Chemical Transformation Simulator (CTS), BioTransformer, UM-Pathway Prediction System (UM-PPS), EnviPath, and US EPA Estimation Programs Interface (EPI) SuiteTM. The simulation provided by these computerized methods is considered parallel to the existing literature data on TPs formed during drinking water processes of water containing the S-Metolachlor as a contaminant. In addition, knowing the structure of the S-Metolachlor TPs, computerized tools can predict the biological activity regarding some of the relevant endpoints for drinking water quality assessment. Various software offers different endpoint-specific models for evaluating the hazard of chemicals: VEGA HUB, which includes VEGA QSAR, ToxRead, ToxWeight, and ToxDelta, ADMET Predictor, Toxtree, MultiCASE, TEST, OSIRIS Property Explorer, OECD QSAR Toolbox, and PASS. The interpretation of the obtained in silico results and their possible contribution to filling data gaps using a Weight of Evidence (WoE) approach will be discussed. This research demonstrates how predictive toxicology can complement traditional exposure and risk assessment practices. In a broader sense, these approaches also can direct cost-effective targeted analysis and improve risk assessment frameworks for chemicals and their derivates, especially if toxicological data are absent or incomplete.”
(Citation: Ferrario, A.S., Reus, S.A., Hofman-Caris, C.H.M., Dingemans, M.M.L. – P04-16 in silico applications for the prediction and hazard assessment of transformation products originated from water disinfection treatment processes – Toxicology Letters 368(2022), p. S105 – DOI: 10.1016/j.toxlet.2022.07.300)
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