Figure 1

Overview of the workflow of different methods for multi-target screening. The example assumes a data set with a main target T1 and a secondary target T2 which should be avoided by the ligand. S V M _Rank (a) and the multi-class SVM (b) learn the encoding s of the activity profile. Separate SVM models (c) predict the activity of i via act(i) and infer distinct classes based on the proposed encoding. The SVM with linear combinations (d) uses subsets of the data set to build several models that are combined before prediction. The encoding s of the desired activity profile is reflected in the factors c of the linear combinations.