SMILES-based deep generative scaffold decorator for de-novo drug design

SMILES-based deep generative scaffold decorator for de-novo drug design

Abstract Molecular generative models trained with small sets of molecules represented as SMILES strings can generate large regions of the chemical space. Unfortunately, due to the sequential nature of SMILES strings, these models are not able to generate molecules given a scaffold (i.e., partially-b...

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Bibliographic Details
Main Authors: Josep Arús-Pous, Atanas Patronov, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist
Format: Article
Language:English
Published: BMC 2020-05-01
Series:Journal of Cheminformatics
Subjects:
Deep learning
Generative models
SMILES
Randomized SMILES
Recurrent neural networks
Fragment-based drug discovery
Online Access:http://link.springer.com/article/10.1186/s13321-020-00441-8

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http://link.springer.com/article/10.1186/s13321-020-00441-8

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