Proteochemometrics or quantitative multi-structure-property-relationship modeling (QM-SPR) is an extension from the traditional quantitative structure-activity relationship (QSAR) modeling. In QSAR, the target protein is fixed and its interaction with ligands (small molecules or compounds) is predicted only from ligands descriptors. On the contrary, the aim of proteochemometrics is to predict the binding a nity value by modeling the interaction of both proteins and ligands. For this, a data matrix is built, each of its rows containing descriptors of both target and ligand linked to some experimentally measured biological activity. A statistical or machine learning method is then used to induce the model. The main advantages over QSAR are twofold: first, that the induced model can be applied for predictions of interaction with new proteins as well as ligands and second, that it can consider the underlying biological information carried by the protein as well as other possible cross-interactions of the ligand.