A Risk Assessment of Human Ether-a-Go-Go-Related Gene Potassium Channel Inhibition by Using Lipophilicity and Basicity for Drug Discovery

Abstract

The blockade of human ether-a-go-go-related gene (hERG) potassium channels is widely regarded as the predominant cause of drug-induced QT prolongation. The correlation analysis between the inhibition of the hERG channel (hERG inhibition) and physicochemical properties was investigated by use of in-house quinolone antibiotics as model compounds. In order to establish a simple prediction model of hERG inhibition, we focused on the comprehensible physicochemical parameters such as lipophilicity (log P) and basicity (pK_a). At first, the risk associated with increasing log P and pK_a was examined by statistical analysis. It was demonstrated that the risk associated with increasing log P and pK_a by one unit, respectively, almost identically increased. Consequently, equal attention should be paid to both parameters on hERG inhibition. Next, a prediction model of hERG inhibition which was represented by log P and pK_a was investigated. As a result, we built the stepwise discriminant prediction model which took advantage of the risk judgment by zone classification. In conclusion, the impact of log P and pK_a on hERG inhibition was clarified relatively and quantitatively. The quantitative risk assessment established based on both parameters, was considered to be a practical and useful tool in avoiding hERG inhibition and in the rational drug design for drug discovery, especially in lead optimization. Moreover, we also carried out a trend analysis using a different derivative and demonstrated that both parameters were equally significant for hERG inhibition.