A synergism of in silico and statistical approaches to discover new potential endocrine disruptor mycotoxins
TOXICOLOGY AND APPLIED PHARMACOLOGY(2022)
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, alpha- and beta-zearalenol, aflatoxin B1, and alternariol have been shown to be putative endocrine disruptors chemicals for nuclear receptors.
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Key words
Endocrine disruptors,Mycotoxins,Nuclear receptors,Molecular docking,Dimension reduction
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