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Updated: May 31, 2026
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In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
The open-access dataset for insilico cardiotoxicity prediction system
Bioinformation
|July 9, 2011
Summary
This study presents a freely available dataset of 263 molecules and 642 records on human ether-à-go-go-related gene (hERG) inhibition, crucial for predicting drug cardiotoxicity early in development.
Area of Science:
- Pharmacology
- Computational Chemistry
- Toxicology
Background:
- Drug-induced cardiotoxicity is a major cause of fatal adverse events and drug withdrawals.
- Early assessment of cardiotoxicity is critical in drug development.
- hERG channel inhibition is a primary mechanism of drug-induced cardiotoxicity.
Purpose of the Study:
- To describe a comprehensive, publicly available dataset for developing predictive models of hERG inhibition.
- To facilitate the development of reliable in silico models for early cardiotoxicity assessment.
Main Methods:
- Compilation of a dataset from peer-reviewed literature.
- Inclusion of hERG inhibition data (IC50 values) for 263 molecules across 642 records.
- Standardization of data from studies using XO, CHO, and HEK cell models and defined electrophysiological settings.
Main Results:
- A robust dataset was curated, suitable for quantitative structure-activity relationship (QSAR) modeling.
- The dataset enabled the successful development of predictive models for hERG inhibition.
- The data provides a valuable resource for researchers in drug safety.
Conclusions:
- The described dataset is a significant resource for advancing in silico cardiotoxicity prediction.
- Availability of this data supports the development of safer drugs by enabling early identification of potential hERG inhibitors.
- This work contributes to reducing drug-related fatalities and withdrawals through improved predictive toxicology.
