Quantitative structure-activity relationships (QSAR) is an area of computational research that builds virtual models to predict quantities such as the binding affinity or the toxic potential of existing or hypothetical molecules. Although a wealth of experimental data emphasizes the active role of the target protein in the binding process, QSAR studies are frequently restricted to the properties of the small-molecule ligand. This review aims at discussing recent QSAR concepts exploring higher dimensions (simulation of induced fit, simultaneous exploration of alternative binding modes, and solvation scenarios), and their benefit for the drug-discovery process.