Discovery of Novel Inhibitors of a Critical Brain Enzyme Using a Homology Model and a Deep Convolutional Neural Network

Rare
neglected diseases may be neglected but are hardly rare, affecting
hundreds of millions of people around the world. Here, we present
a hit identification approach using AtomNet, the world’s first
deep convolutional neural network for structure-based drug discovery,
to identify inhibitors targeting aspartate N-acetyltransferase
(ANAT), a promising target for the treatment of patients suffering
from Canavan disease. Despite the lack of a protein structure or high
sequence identity homologous templates, the approach successfully
identified five low-micromolar inhibitors with drug-like properties.