DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network
Fig 5
ROC plots evaluating the performance of DeepDrug3D and other methods to classify ligand-binding sites.
DeepDrug3D is compared to pocket matching with G-LoSA, molecular docking with Vina, and sequence signature detection with ScanProsite for (A) nucleotide- and (B) heme-binding pockets. The x-axis shows the false positive rate (FPR) and the y-axis shows the true positive rate (TPR). The gray area represents a random prediction.