As the product can be represented by the deterministic function g(S|G) of S, Y can be expressed by a function of S as Y = f (S|G). Here, Y can be a vector of one or more properties. Function h can be specified arbitrary; for example, a machine learning property prediction model or a scoring function such as the quantitative estimate of drug-likeness (QED) score .