Abstract

Quantitative Structure-Activity Relationships are widely acknowledged predictive methods employed, for years, in organic and medicinal chemistry. More recently, they have assumed a central role also in the context of the explorative toxicology for the protection of environment and human health. However, their real-life application has not been always enthusiastically welcomed, being often retrospectively used and, thus, of limited importance for prospective goals. The need of making more trustable predictions has thus addressed studies on the so-called Applicability Domain, which represents the chemical space from which a model is derived and where a prediction is considered to be reliable. In the present study, the authors survey a number of approaches used to build the Applicability Domain. In particular, they will focus on strategies based on: a) physico-chemical, b) structural and c) response domains. Moreover, some examples integrating different strategies will be also discussed to meet the needs of both model developers and downstream users.