Prediction of hERG inhibition of drug discovery compounds using biomimetic HPLC measurements

Abstract

The major causes of failure of drug discovery compounds in clinics are the lack of efficacy and toxicity. To reduce late-stage failures in the drug discovery process, it is essential to estimate early the probability of adverse effects and potential toxicity. Cardiotoxicity is one of the most often observed problems related to a compound's inhibition of the hERG channel responsible for the potassium cation flux. Biomimetic HPLC methods can be used for the early screening of a compound's lipophilicity, protein binding and phospholipid partition. Based on the published hERG pIC50 data of 90 marketed drugs and their measured biomimetic properties, a model has been developed to predict the hERG inhibition using the measured binding of compounds to alpha-1-acid-glycoprotein (AGP) and immobilised artificial membrane (IAM). A representative test set of 16 compounds was carefully selected. The training set, involving the remaining compounds, served to establish the linear model. The mechanistic model supports the hypothesis that compounds have to traverse the cell membrane and bind to the hERG ion channel to cause the inhibition. The AGP and the hERG ion channel show structural similarity, as both bind positively charged compounds with strong shape selectivity. In contrast, a good IAM partition is a prerequisite for cell membrane traversal. For reasons of comparison, a corresponding model was derived by replacing the measured biomimetic properties with calculated physicochemical properties. The model established with the measured biomimetic binding properties proved to be superior and can explain over 70% of the variance of the hERG pIC50 values.

Keywords: AGP binding; Cardiotoxicity; IAM binding; Proarrhythmia; QT Prolongation; Torsades de Pointes; hERG inhibition.

Figure 1

The score plot from the principal component analysis on the calculated properties. Compounds served as the test set are marked in red, as follows: (1) dofetilide, (2) sildenafil, (3) irbesartan, (4) flecainide, (5) ziprasidone, (6) trazodone, (7) fluoxetine, (8) protryptiline, (9) diphenhydramine, (10) desloratanide, (11) spironolactone, (12) metoprolol, (13) lamotrigine, (14) indomethacin, (15) trimethoprim, (16) alfuzosin.

Figure 2

shows the literature hERG pIC₅₀ data and the back-calculated pIC₅₀ data using equation 3. Blue circles mark positively charged compounds at pH 7.4; red circles mark negatively charged compounds at pH7.4. The green circles mark neutral compounds at pH 7.4; green circle’s shade reflects the presence of weak acidic (lighter green) or weak basic (darker green) groups in the molecules; purple circles indicate compounds with zwitterionic character at pH 7.4

Figure 3.

The similarity of the binding region of AGP and hERG potassium ion channels.

Figure 4.

Drug trapping within the K1 channel vestibule.