Previous research into protein-ligand interaction prediction has established that grouping data from multiple protein targets improves performance. These proteochemometric (PCM) models make use of similarities and dissimilarities between proteins in addition to the compound structures used in the target-specific quantitative structure-activity relationship (QSAR) models. This way, the addition of target information increases both model performance and types of applications (for example to extend modeling to several protein targets simultaneously or the inclusion of genetic variants).