Nuclear Receptors: From Drugs to Food, and from In Silico to In Vitro

Abstract

In silico techniques are an emerging field in Food Science. In silicomeans done using computer, also defined as dry experiments while traditional lab experiments are commonly defined as wet experiments. These techniques come from Medicinal Chemistry and Computational Chemistry where they have been known for many decades. Common applications of informatics techniques in Food Science are traditionally statistics and QSAR (Quantitative Structure Activity Relationship) approaches. However, massive screening of databases of chemicals, docking and scoring of most promising chemicals into known receptors are not common applications in food science, i.e. food safety, food security, food toxicology, predictive toxicology, etc. One of the most important questions we would like to answer is: could we merge in silico and in vitro tests for a better food safety? Because we live in a world of chemicals where more than 110 million chemical compounds are known to exist to date (source: CAS, Chemical abstract Service), we are exposed to many of these chemicals during our lifetime. Unfortunately, it is not realistic to think we can check the safety of such huge number of compounds. If indeed it is true that humans produce about 500∼1000 chemicals every year, we have to be conscious about the potential of some of them to negatively affect our metabolic and physiological pathways, and about the possibility to encounter potential disruptors in our daily life. Unfortunately, this huge number of chemicals is too big to be investigated by means of standard experimental approaches, as in vitro and in vivo test, in particular if we consider the number of possible associated metabolites. Computational methods could represent a valuable alternative to dramatically reduce the number of potential disruptors to be experimentally tested. Nuclear Receptors represent an important class of potential targets for medicinal chemistry and food safety; thus, computational techniques, widely applied in medicinal chemistry field, can represent valuable tools also in food science. Food additives, food contact materials, mycotoxins, plasticizers and their metabolites can interact with this class of receptors acting as endocrine disruptors. In silicomethods can predict these potential interactions between a ligand (food additive, mycotoxins, food contact material, etc.) and a receptor of known 3D structure, representing a unique way to test the effect of a huge amount of chemicals without in vitro tests. In vitro tests must be applied only for molecules predicted as good possible interactors. It should be stated, however, that in silico interaction prediction is not an absolute certainty of the real activation of the receptor made by the ligand, where binding of a ligand within a cavity of a receptor is not always synonymous with a receptor activation, it is necessary to understand the whole complex biochemical pathway.