Deep learning, an emerging field of artificial intelligence based on neural networks in machine learning,
has been applied in various fields and is highly valued. Herein, we mainly review several mainstream architectures
in deep learning, including deep neural networks, convolutional neural networks and recurrent neural
networks in the field of drug discovery. The applications of these architectures in molecular de novo design,
property prediction, biomedical imaging and synthetic planning have also been explored. Apart from that, we
further discuss the future direction of the deep learning approaches and the main challenges we need to address.