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In silico prediction of hERG inhibition
Yankang Jing1, Alison Easter, David Peters
1Biogen Idec, 250 Binney Street, Cambridge, MA 02142, USA.
Future Medicinal Chemistry
|April 30, 2015
Summary
hERG channel screening is vital for drug safety, as blocking this channel prolongs cardiac action potentials and can cause sudden death. Computational models offer a fast, cost-effective method for early drug discovery screening.
Area of Science:
- Cardiovascular Pharmacology
- Computational Chemistry
- Drug Discovery
Background:
- The hERG channel is crucial for cardiac repolarization, controlling the delayed rectifying potassium current (IKr).
- Blockade of the hERG channel prolongs the QT interval, increasing the risk of fatal arrhythmias and leading to drug withdrawal.
- Early screening for hERG channel interactions is essential for drug development safety.
Purpose of the Study:
- To review and classify computational in silico prediction models for hERG channel activity.
- To highlight the importance of hERG screening in early drug discovery to prevent adverse cardiac events.
Main Methods:
- Classification of hERG prediction models into distinct categories.
- Discussion of quantitative structure-activity relationship (QSAR) models (2D and 3D).
- Inclusion of pharmacophore, classification, and structure-based (homology modeling) approaches.
Main Results:
- Computational models provide a rapid and economical approach for screening drug candidates.
- Various in silico models exist for predicting hERG channel interactions, aiding in risk assessment.
Conclusions:
- In silico hERG screening is a valuable tool in early drug discovery, mitigating risks associated with cardiotoxicity.
- The reviewed models (2D/3D QSAR, pharmacophore, classification, structure-based) offer diverse strategies for predicting hERG liability.
