Prediction of hERG potassium channel affinity by traditional and hologram qSAR methods

Traditional and hologram QSAR (HQSAR) models were developed for the prediction of hERG potassium channel affinities. The models were validated on three different test sets including compounds with published patch-clamp IC 50 data and two subsets from the World Drug Index (compounds indicated to have ECG modifying adverse effect and drugs marked to be approved, respectively). Discriminant analysis performed on the full set of hERG data resulted in a traditional QSAR model that classified 83% of actives and 87% of inactives correctly. Analysis of our HQSAR model revealed it to be predictive in both IC 50 and discrimination studies. Discriminant analysis of 68 compounds with reported hERG K+ channel affinity resulted in a traditional QSAR model that classified 83% of actives and 87% of inactives correctly. The HQSAR model predicted patch-clamp IC 50 values with reasonable accuracy and was found to be useful in discrimination studies evaluating large datasets.