|
Abstract : |
Abstract. This paper is a case study of a machine aided knowledge discovery process within the general area of drug design. More specifically, the paper describes a sequence of experiments in which an Inductive Logic Programming(ILP) system is used for pharmacophore discovery. Within drug design, a pharmacophore is a description of the substructure of a ligand (a small molecule) which is responsible for medicinal activity. This medicinal activity is produced by interaction between the ligand and a binding site on a target protein. ILP was chosen by the domain expert (first author) at Pfizer since active molecules are most naturally described, in relational terms, as requiring a substructure (pharmacophore) with various 3-D relations which hold among the atoms involved. The results described in this paper build on previous investigations into prediction of mutagenicity using ILP with a 2-D (bond connectivity only) representation of molecules. The case study supports general lessons for knowledge discovery, as well as more specific lessons for pharmacophorediscovery, the use of ILP for 3-D problems, and for the particular medicinal activity of ACE inhibition, a treatment for hypertension., |
