Machine learning and deep learning approaches for enhanced prediction of hERG blockade: a comprehensive QSAR modeling study.

Jie LiuMd Kamrul Hasan KhanWenjing GuoFan DongWeigong GeChaoyang ZhangPing GongTucker A PattersonHuixiao Hong

Published in: Expert opinion on drug metabolism & toxicology (2024)

The developed models can assist the pharmaceutical industry and regulatory agencies in predicting hERG blockage activity, thereby enhancing safety assessments and reducing the risk of adverse cardiac events associated with new drug candidates.

Keyphrases

machine learning
deep learning
artificial intelligence
molecular docking
transcription factor
molecular dynamics
adverse drug
big data
drug induced
structure activity relationship