The prediction of a ligand's binding mode into its macromolecular target is essential in structure-based drug discovery. Even though tremendous effort has been made to address this problem, most of the developed tools work similarly, trying to predict the binding free energy associated with each particular binding mode. In this study, we decided to abandon this criterion, following structural stability instead. This view, implemented in a novel computational workflow, quantifies the steepness of the local energy minimum associated with each potential binding mode. Surprisingly, the protocol outperforms docking scoring functions in case of fragments (ligands with MW < 300 Da) and is as good as docking for drug-like molecules. It also identifies substructures that act as structural anchors, predicting their binding mode with particular accuracy. The results open a new physical perspective for binding mode prediction, which can be combined with existing thermodynamic-based approaches.