Efficient substructure feature encoding based on graph neural network blocks for drug-target interaction prediction

BackgroundPredicting drug-target interaction (DTI) is a crucial phase in drug discovery. The core of DTI prediction lies in appropriate representations learning of drug and target. Previous studies have confirmed the effectiveness of graph neural networks (GNNs) in drug compound feature encoding. Ho...

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Principais autores:	Guojian Deng, Changsheng Shi, Ruiquan Ge, Riqian Hu, Changmiao Wang, Feiwei Qin, Cheng Pan, Haixia Mao, Qing Yang
Formato:	Artigo
Idioma:	Inglês
Publicado:	Frontiers Media S.A. 2025-03-01
Series:	Frontiers in Pharmacology
Assuntos:	graph neural network drug discovery graph representation learning molecular substructure drug-target interaction prediction
Acceso en liña:	https://www.frontiersin.org/articles/10.3389/fphar.2025.1553743/full
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