Investigation of miscellaneous hERG inhibition in large diverse compound collection using automated patch-clamp assay

Abstract

Aim: hERG potassium channels display miscellaneous interactions with diverse chemical scaffolds. In this study we assessed the hERG inhibition in a large compound library of diverse chemical entities and provided data for better understanding of the mechanisms underlying promiscuity of hERG inhibition.

Methods: Approximately 300 000 compounds contained in Molecular Library Small Molecular Repository (MLSMR) library were tested. Compound profiling was conducted on hERG-CHO cells using the automated patch-clamp platform-IonWorks Quattro(™).

Results: The compound library was tested at 1 and 10 μmol/L. IC50 values were predicted using a modified 4-parameter logistic model. Inhibitor hits were binned into three groups based on their potency: high (IC50<1 μmol/L), intermediate (1 μmol/L< IC50<10 μmol/L), and low (IC50>10 μmol/L) with hit rates of 1.64%, 9.17% and 16.63%, respectively. Six physiochemical properties of each compound were acquired and calculated using ACD software to evaluate the correlation between hERG inhibition and the properties: hERG inhibition was positively correlative to the physiochemical properties ALogP, molecular weight and RTB, and negatively correlative to TPSA.

Conclusion: Based on a large diverse compound collection, this study provides experimental evidence to understand the promiscuity of hERG inhibition. This study further demonstrates that hERG liability compounds tend to be more hydrophobic, high-molecular, flexible and polarizable.

Figure 1

Seal resistance and current expression of hERG-CHO stable cell line measured using the IonWorks Quattro^™ system. (A) Recording protocols and the typical hERG current traces in the absence and presence of 1 μmol/L Dofetilide. In the displayed protocol, the solid line represented the protocol used for majority of compounds while the dashed line presented a voltage pulse used in a small fraction of compounds of the screening. Dose-response curve for Dofetilide is displayed in the right panel. (B) Histograms of seal resistance recorded across 384 wells of single-hole (HT) (black color filled bars) and population patch clamp (PPC) (grey color filled bars) using hERG-CHO cells at a density 1.8×10⁶ cells/mL. The bootstrap analysis was applied to the data from single-hole mode to simulate the distribution of seal resistance in the PPC mode (as shown in the unfilled bars). (C) The distribution of the seal resistance (PPC mode) for the screened library with the mean±SD values at 89.66±36.26 Mohms. (D) Histograms of peak tail current amplitude obtained from single-hole (black color filled bars) and PPC modes (grey color filled bars). Peak currents at the first test pulse were measured in each well. Similar to the seal resistance, the bootstrap analysis was performed to estimate the distribution of hERG tail current on PPC mode using experimental results from the single-hole mode (as shown in unfilled bars). (E) The distribution of the peak currents (PPC mode) for the screened library with the mean±SD values at 0.62±0.17 nA.

Figure 2

Success rate of the hERG primary screening using automated patch clamp assay. Cells with peak tail current amplitude bigger than 0.2 nA, seal resistance more than 30 MOhms, and percentage reduction of seal resistance (caused by first or second compound addition) lower than 25% were included for data analysis. MLSMR library 318 950 compounds in 1008 384-well compounds plates were screened. The averaged success rate was 96.08%±2.45%.

Figure 3

Data stability of the dual additions for seal resistance and hERG peak tail currents. The histograms of seal resistance and hERG currents are shown in (A) and (B). Seal resistance change (%) was determined by the formula 100 %^*[(R_post-1-R_pre)/R_pre] (first addition) and 100 %^*[(R_post-2-R_pre)/R_pre] (second addition) from the compound treated wells, which are represented as mean±SD values of 6.63±9.13 (%) and 5.55±12.56 (%), respectively. And the tail current change (%) was calculated by the formula 100%^*[(I_post-1-I_pre)/I_pre] (first addition) and 100%^*[(I_post-2-I_pre)/I_pre] (second addition) from the vehicle treated wells, which are represented as mean±SD values of −8.87%±7.54% and −13.99%±11.84%. The histogram distribution of Z′ factor and signal noise ratio for the first addition are shown in the upper panels of (C) and (D). The data exhibited mean±SD values of 0.70±0.09 (Z′ factor) and 14.72±4.60 (signal-to-noise ratio), respectively. For the second addition, the mean±SD values are 0.64±0.10 (Z′ factor) (lower panel of C) and 11.47±3.45 (signal-to-noise ratio) (lower panel of D), respectively.

Figure 4

Correlation between the same compounds but distributed in different plates. Within the MLSMR collection, we acquired data for 85 pairs of identical compounds but distributed in different plates, including two known hERG inhibitors, Pyrilamine (grey color filled circle) and Chlorpheniramine (black color filled circle). For the 85 pair of compounds, the correlation efficient is 0.79 and 0.88 for the peak tail current change at 1 μmol/L (A) and 10 μmol/L (B).

Figure 5

Linear regression analysis to assess the mathematical prediction for the IC₅₀. The R value is 0.90 and 0.95 respectively for 1 μmol/L (A) and 10 μmol/L (B) for the one-point method. Further the relationship between the percent inhibition and Log10 (IC₅₀) from the weighed method was generated. R value is 0.89 (at 1 μmol/L) (C) and 0.91 (at 10 μmol/L) (D).

Figure 6

Summary of MLSMR compound library on hERG channels. (A) Distribution of compound effects on peak tail current. Black bars are for tail current percentage change at 1 μmol/L and red bars are for 10 μmol/L. (B) Effects of inhibitor select criteria on hit rates. hERG inhibitors were ranked based on their IC₅₀s calculated using weighed 1-point method based on the two hit selection criteria (Mean of Control-3SD or Mean of Control-5SD) at 10 μmol/L. Black box: IC₅₀<=1 μmol/L; grey box: 1 μmol/L<IC₅₀<=10 μmol/L; light grey box: IC₅₀>10 μmol/L; white box: inactive. (C) Correlation of compound effects at 1 μmol/L and 10 μmol/L. The scatter plot of tail current change for each tested compound at 1 μmol/L (horizontal axis) and 10 μmol/L (Vertical axis), is color-coded by the potency classes. Black filled circles indicate inhibitors with IC₅₀<=1 μmol/L; grey filled circles indicate inhibitors with IC₅₀ between 1 μmol/L and 10 μmol/L; light grey filled circles indicate inhibitors with IC₅₀>10 μmol/L with the cutoff at mean-3SD of vehicle control at 10 μmol/L; open circles indicate hERG activators and inactive compounds. (D) Correlation between the predicted and literature reported IC₅₀ for 74 known hERG inhibitors.

Figure 7

Effect of compound physiochemical properties on hERG inhibitors and non-hERG inhibitors. (A) Octanol-water partition coefficient (ALogP); (B) Molecular weight (MW); (C) Rotatable bond number (RTB); (D) Hydrogen bond acceptor number (HBA); (E) Hydrogen bond donor number (HBD); (F) Topological polar surface area (TPSA); (G) Bar chart for the comparison between hERG active and inactive compounds. ^cP<0.01, student t-test. “Active” represents hERG inhibitors passing the statistical threshold (mean-3 SD) of vehicle control at 10 μmol/L; “Inactive” is for those compounds not passing the statistical threshold (mean-3 SD) of vehicle control at 10 μmol/L.

Figure 8

Compound physiochemical properties affected potency of hERG inhibitors. (A) Octanol-water partition coefficient (ALogP); (B) Molecular weight (MW); (C) Rotatable bond number (RTB); (D) Hydrogen bond acceptor number (HBA); (E) Hydrogen bond donor number (HBD); (F) Topological polar surface area (TPSA). Dark blue bar: IC₅₀<1 μmol/L; pink bar: 1 μmol/L<IC₅₀<10 μmol/L; light blue bar: IC₅₀>10 μmol/L; grey bar: hERG inactive compounds; white bar: hERG inactive compounds.