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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Bibliographic Details

Published in:	Frontiers in Pharmacology
Main Authors:	Guojian Deng, Changsheng Shi, Ruiquan Ge, Riqian Hu, Changmiao Wang, Feiwei Qin, Cheng Pan, Haixia Mao, Qing Yang
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-03-01
Subjects:	graph neural network drug discovery graph representation learning molecular substructure drug-target interaction prediction
Online Access:	https://www.frontiersin.org/articles/10.3389/fphar.2025.1553743/full