DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network
Fig 1
Voxelization of ligand-binding pockets.
(A) Starting from a ligand-protein complex, a sphere centered on the geometric center of the ligand is created and filled with a 3D grid. Grid points (B) overlapping with the protein, (C) too far away from the protein, and (D) disconnected from the main grid structure are removed. Points to be removed are shown in red in B-D. Subsequently, (E) statistical potentials for ligand-protein interactions are calculated at each grid point and (F) the pocket principal axes are aligned to the Cartesian axes. (G) The voxel representation of a ligand-binding pocket is used as an input in deep learning.