Predictive models for hERG potassium channel blockers

We report here a general method for the prediction of hERG potassium channel blockers using computational models generated from correlation analyses of a large dataset and pharmacophore-based GRIND descriptors. These 3D-QSAR models are compared favorably with other traditional and chemometric based HQSAR methods.

Computational QSAR models constructed from pharmacophore-based GRIND descriptors were found to be predictive for hERG channel blockers.Figure optionsDownload as PowerPoint slide