Fig. 1: The flowchart of EviDTI.
From: Evidential deep learning-based drug-target interaction prediction
For a given drug-target pair, the protein feature encoder employs the pre-trained ProtTrans for initial target representation, further refined by a light attention (LA) module. The drug feature encoder processes the 2D topology and 3D structure representations. The 2D representation is derived from the pre-trained MG-BERT model and processed by 1D CNN. The 3D structure representation is obtained via the GeoGNN. These representations are concatenated and fed into the evidence layer, which outputs parameter α for prediction probability and uncertainty.
