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• W4200505772 startingPage "115832" @default.
• W4200505772 abstract "Mycotoxins are secondary metabolites produced by pathogenic fungi. They are found in a variety of different products, such as spices, cocoa, and cereals, and they can contaminate fields before and/or after harvest and during storage. Mycotoxins negatively impact human and animal health, causing a variety of adverse effects, ranging from acute poisoning to long-term effects. Given a large number of mycotoxins (currently more than 300 are known), it is impossible to use in vitro/in vivo methods to detect the potentially harmful effects to human health of all of these. To overcome this problem, this work aims to present a new robust computational approach, based on a combination of in silico and statistical methods, in order to screen a large number of molecules against the nuclear receptor family in a cost and time-effective manner and to discover the potential endocrine disruptor activity of mycotoxins. The results show that a high number of mycotoxins is predicted as a potential binder of nuclear receptors. In particular, ochratoxin A, zearalenone, α- and β-zearalenol, aflatoxin B1, and alternariol have been shown to be putative endocrine disruptors chemicals for nuclear receptors." @default.
• W4200505772 created "2021-12-31" @default.
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• W4200505772 date "2022-01-01" @default.
• W4200505772 modified "2023-09-24" @default.
• W4200505772 title "A synergism of in silico and statistical approaches to discover new potential endocrine disruptor mycotoxins" @default.
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• W4200505772 doi "https://doi.org/10.1016/j.taap.2021.115832" @default.
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