Prediction of hERG K+ blocking potency: application of structural knowledge

Area of Science:

• Cardiovascular Pharmacology
• Computational Chemistry
• Drug Safety Assessment

Background:

• QT-prolongation is a serious adverse drug reaction affecting cardiac repolarization.
• hERG K+ channel blockade is a primary mechanism underlying drug-induced QT-prolongation.
• Predictive modeling is crucial for early identification of cardiotoxic drug candidates.

Purpose of the Study:

• To develop and validate a Quantitative Structure-Activity Relationship (QSAR) model for predicting hERG K+ channel blocking activity.
• To identify key molecular descriptors influencing QT-prolongation.
• To assess the predictive performance and stability of the developed QSAR model.

Main Methods:

• Utilized a dataset of 19 structurally diverse drugs known to block the hERG K+ channel.
• Employed hydrophobicity corrected for ionization (log D) and various 2D/3D molecular descriptors.
• Applied stepwise regression to build the QSAR model and employed scrambling and external validation for robustness assessment.

Main Results:

• A two-parameter QSAR model incorporating log D and maximum molecular diameter (Dmax) was developed with good statistical fit.
• Model validation using scrambling and external sets confirmed its stability and statistical significance.
• The study highlights the impact of molecular size on the QT-prolongation side effect.

Conclusions:

• The developed QSAR model provides a transparent and interpretable tool for predicting hERG K+ channel blockade.
• Hydrophobicity and molecular size are significant predictors of QT-prolongation risk.
• This model can aid in the early-stage drug safety evaluation of potential hERG K+ channel blocking agents.