Chemical variational autoencoder (VAE) is a deep learning method for constructing chemical latent spaces, however, the current chemical VAE variants are limited in their ability to handle complex compound structures like natural products. Here, the authors develop a variational autoencoder that can handle natural products and demonstrate its utility as an in silico drug discovery tool.
- Toshiki Ochiai
- Tensei Inukai
- Yasubumi Sakakibara