A de novo molecular generation method using latent vector based generative adversarial network.
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ABSTRACT:
SUBMITTER: Prykhodko O
PROVIDER: S-EPMC6892210 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature
Publications
A de novo molecular generation method using latent vector based generative adversarial network.
Prykhodko Oleksii O Johansson Simon Viet SV Kotsias Panagiotis-Christos PC Arús-Pous Josep J Bjerrum Esben Jannik EJ Engkvist Ola O Chen Hongming H
Journal of cheminformatics 20191203 1
Deep learning methods applied to drug discovery have been used to generate novel structures. In this study, we propose a new deep learning architecture, LatentGAN, which combines an autoencoder and a generative adversarial neural network for de novo molecular design. We applied the method in two scenarios: one to generate random drug-like compounds and another to generate target-biased compounds. Our results show that the method works well in both cases. Sampled compounds from the trained model ...[more]
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