To enable VS, we supplemented DiffDock-L's pose sampling and scoring capabilities with the Vina scoring function (AutoDock Vina package ) and Gnina scoring function. The two scoring functions are among the most popular representatives of classical and DL-based scoring functions, respectively. We test the VS performance of the integrated approach on the E-Z benchmark data set and compare it to the performance of AutoDock Vina as a reference method for classical docking approaches. 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). 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 classical docking approach.