Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency
Fig 3
A light graph-learning architecture adopted in this work.
The node feature matrix F and inter-molecular adjacency tensor A of a protein-ligand complex are the inputs, and the binding strength is the output. Main components of this architecture include graph convolution layers, node aggregation layers, dense (fully-connected) layers and dropout layers.