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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Using In Silico Approach for Metabolomic and Toxicity Prediction of Alternariol
Daniela Eliza Marin1, Ionelia Taranu1
1National Research and Development Institute for Biology and Animal Nutrition, 077015 Balotesti, Romania.
Abstract:
Alternariol is a metabolite produced by Alternaria fungus that can contaminate a variety of food and feed materials. The objective of the present paper was to provide a prediction of Phase I and II metabolites of alternariol and a detailed ADME/Tox profile for alternariol and its metabolites using an in silico working model based on the MetaTox, SwissADME, pKCMS, and PASS online computational programs. A number of 12 metabolites were identified as corresponding to the metabolomic profile of alternariol. ADME profile for AOH and predicted metabolites indicated a moderate or high intestinal absorption probability but a low probability to penetrate the blood-brain barrier. In addition to cytotoxic, mutagenic, carcinogenic, and endocrine disruptor effects, the computational model has predicted other toxicological endpoints for the analyzed compounds, such as vascular toxicity, haemato-toxicity, diarrhea, and nephrotoxicity. AOH and its metabolites have been predicted to act as a substrate for different isoforms of phase I and II drug-metabolizing enzymes and to interact with the response to oxidative stress. In conclusion, in silico methods can represent a viable alternative to in vitro and in vivo tests for the prediction of mycotoxins metabolism and toxicity.

