The goal of chemogenomics is the exploration of all possible interactions between compounds from the chemical space and targets from the biological space. This huge interaction matrix is only sparsely filled with experimental data but can be complemented by predicted values for selected ligand–target pairs. The prediction by computational chemogenomics uses the similarity principle that states that similar compounds have similar properties and that targets with similar binding sites bind similar ligands. Chemogenomics has a number of interesting applications, e.g. the prediction of the bioprofile of drugs including an assessment of possible adverse drug effects or the support of phenotypic screening by target fishing. This review focuses on applications of computational chemogenomics in pharmaceutical research and on the role that it plays in an industrial environment.