AttenhERG: a reliable and interpretable graph neural network framework for predicting hERG channel blockers

AttenhERG: a reliable and interpretable graph neural network framework for predicting hERG channel blockers

Abstract Cardiotoxicity, particularly drug-induced arrhythmias, poses a significant challenge in drug development, highlighting the importance of early-stage prediction of human ether-a-go-go-related gene (hERG) toxicity. hERG encodes the pore-forming subunit of the cardiac potassium channel. Tradit...

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Bibliographic Details
Main Authors: Tianbiao Yang, Xiaoyu Ding, Elizabeth McMichael, Frank W. Pun, Alex Aliper, Feng Ren, Alex Zhavoronkov, Xiao Ding
Format: Article
Language:English
Published: BMC 2024-12-01
Series:Journal of Cheminformatics
Subjects:
Cardiotoxicity
hERG prediction
Graph neural network
Attention mechanism
Online Access:https://doi.org/10.1186/s13321-024-00940-y

Internet

https://doi.org/10.1186/s13321-024-00940-y

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