DGDTA: dynamic graph attention network for predicting drug–target binding affinity

DGDTA: dynamic graph attention network for predicting drug–target binding affinity

Abstract Background Obtaining accurate drug–target binding affinity (DTA) information is significant for drug discovery and drug repositioning. Although some methods have been proposed for predicting DTA, the features of proteins and drugs still need to be further analyzed. Recently, deep learning h...

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Bibliographic Details
Main Authors: Haixia Zhai, Hongli Hou, Junwei Luo, Xiaoyan Liu, Zhengjiang Wu, Junfeng Wang
Format: Article
Language:English
Published: BMC 2023-09-01
Series:BMC Bioinformatics
Subjects:
Drug–target binding affinity
Dynamic graph attention network
Long short-term memory
Drug discovery
Online Access:https://doi.org/10.1186/s12859-023-05497-5

Internet

https://doi.org/10.1186/s12859-023-05497-5

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