Interactive Discriminative Mining of Chemical Fragments

Abstract. Structural activity prediction is one of the most important tasks in chemoinformatics. The goal is to predict a property of interest given structural data on a set of small compounds or drugs. Ideally, systems that address this task should not just be accurate, they should also be able to identify an interpretable discriminative structure which describes the most discriminant structural elements with respect to some target. The application of ILP in an interactive software for discriminative min-ing of chemical fragments is presented in this paper. In particular, it is described the coupling of an ILP system with a molecular visualisa-tion software that allows a chemist to graphically control the search for interesting patterns in chemical fragments. Furthermore, we show how structural information, such as rings, functional groups like carboxyl, amine, methyl, ester, etc are integrated and exploited in the search