Graph-based generative models for de Novo drug design.
Drug Discov Today Technol
; 32-33: 45-53, 2019 Dec.
Article
em En
| MEDLINE
| ID: mdl-33386094
ABSTRACT
The discovery of new chemical entities is a crucial part of drug discovery, which requires the lead compounds to have desired properties to be pharmaceutically active. De novo drug design aims to generate and optimize novel ligands for macromolecular targets from scratch. The development of graph-based deep generative neural networks has provided a new method. In this review, we gave a brief introduction to graph representation and graph-based generative models for de novo drug design, summarized them as four architectures, and concluded each's characteristics. We also discussed generative models for scaffold- and fragment-based design and graph-based generative models' future directions.
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1
Base de dados:
MEDLINE
Assunto principal:
Preparações Farmacêuticas
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Desenho de Fármacos
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Modelos Moleculares
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Descoberta de Drogas
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article