GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity

GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity

Abstract Background Drug-target binding affinity (DTA) prediction is vital in drug discovery and repositioning, more and more researchers are beginning to focus on this. Many effective methods have been proposed. However, some current methods have certain shortcomings in focusing on important nodes...

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Bibliographic Details
Main Authors: Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Genomics
Subjects:
Drug-target binding affinity
Graph neural networks
Transformer
Online Access:https://doi.org/10.1186/s12864-025-11234-4
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