A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
A De Novo Molecular Generation Method Using Latent Vector Based Generative Adversarial Network
[post]
2019
unpublished
<p> </p><p>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
doi:10.26434/chemrxiv.8299544.v4
fatcat:y4kyy46sgfbyvhqs2ju3iwlfcq