We evaluate the VS performance of the approach integrating DiffDock-L on the DUDE-Z benchmark data set and compare it to AutoDock Vina (from here on referred to as 'Vina'). DUDE-Z is the third and latest generation of a well-established data set for testing structure-based algorithms for their VS capacity. The benchmark data set covers 43 structurally diverse and pharmaceutically relevant proteins, including kinases, proteases, G protein-coupled receptors (GPCRs), and nuclear receptors (see Methods for details). Vina is one of the most widely employed physics-based docking methods. Figure . VS pipeline integrating DiffDock-L for pose sampling with the Vina and Gnina scoring functions for compound ranking. AutoDock Vina serves as a reference method for comparing the integrated approach with a physics-based docking approach.