Classification of blocker and non-blocker of hERG potassium ion channel using a support vector machine

Abstract

The human ether-a-go-go related gene (hERG) channel is responsible for the repolarization during the action potential, and blockage of that may result in severe cardiotoxicity and sudden death. In this study, a dataset containing 1969 compounds was compiled from literature and FDA-approved drugs. Using a support vector machine (SVM), two groups of computational models were built to distinguish whether a compound is a blocker or non-blocker of hERG potassium ion channel. These models fit generally satisfactory. The 100 models built with MACCS fingerprints (Model Group A) showed an average accuracy of 90% and an average matthews correlation coefficient (MCC) value of 0.77 on the test sets. The 100 models built with selected MOE descriptors (Model Group B) showed an average accuracy of 89% and an average MCC value of 0.74 on the test sets. Molecular hydrophobicity and lipophilicity were found to be very important factors which lead to block the hERG potassium ion channel. Some other molecular properties such as electrostatic properties, features based on van der Waals surface area, the number of rigid bonds and molecular surface rugosity also played important roles in blocking hERG potassium ion channel.