To establish a binding affinity threshold for selection of promising generated molecules, we initially applied the BUTINA clustering algorithm to our QSAR training dataset to identify representative centroids of active molecules targeting VEGFR-2. Molecules whose pIC 50 values were greater than or equal to 6.0 were considered active. Centroids together with sorafenib (molecule in the 4ASD complex) were then used to create decoys using DeepCoy 32 with an active-inactive ratio of 1:50. Active molecules along with decoys were then docked using Vina-GPU 2.0 software to obtain binding affinity cutoffs. The optimal threshold was determined to be the binding affinity cutoff of the highest geometric mean (g-mean) value corresponding to a certain scoring type. Generated molecules with binding affinity values better than the threshold were selected.