Generative AI for graph-based drug design: Recent advances and the way forward.
Curr Opin Struct Biol
; 84: 102769, 2024 02.
Article
em En
| MEDLINE
| ID: mdl-38199072
ABSTRACT
Discovering new promising molecule candidates that could translate into effective drugs is a key scientific pursuit. However, factors such as the vastness and discreteness of the molecular search space pose a formidable technical challenge in this quest. AI-driven generative models can effectively learn from data, and offer hope to streamline drug design. In this article, we review state of the art in generative models that operate on molecular graphs. We also shed light on some limitations of the existing methodology and sketch directions to harness the potential of AI for drug design tasks going forward.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Desenho de Fármacos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Curr Opin Struct Biol
Assunto da revista:
BIOLOGIA MOLECULAR
Ano de publicação:
2024
Tipo de documento:
Article
País de publicação:
Reino Unido