Graph neural networks for automated de novo drug design.
Drug Discov Today
; 26(6): 1382-1393, 2021 06.
Article
en En
| MEDLINE
| ID: mdl-33609779
ABSTRACT
The goal of de novo drug design is to create novel chemical entities with desired biological activities and pharmacokinetics (PK) properties. Over recent years, with the development of artificial intelligence (AI) technologies, data-driven methods have rapidly gained in popularity in this field. Among them, graph neural networks (GNNs), a type of neural network directly operating on the graph structure data, have received extensive attention. In this review, we introduce the applications of GNNs in de novo drug design from three aspects molecule scoring, molecule generation and optimization, and synthesis planning. Furthermore, we also discuss the current challenges and future directions of GNNs in de novo drug design.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Diseño de Fármacos
/
Redes Neurales de la Computación
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Drug Discov Today
Asunto de la revista:
FARMACOLOGIA
/
TERAPIA POR MEDICAMENTOS
Año:
2021
Tipo del documento:
Article
País de afiliación:
China