Molecular Dynamics-Derived Pharmacophore Model Explaining the Nonselective Aspect of KV10.1 Pore Blockers

Abstract

The KV10.1 voltage-gated potassium channel is highly expressed in 70% of tumors, and thus represents a promising target for anticancer drug discovery. However, only a few ligands are known to inhibit KV10.1, and almost all also inhibit the very similar cardiac hERG channel, which can lead to undesirable side-effects. In the absence of the structure of the KV10.1–inhibitor complex, there remains the need for new strategies to identify selective KV10.1 inhibitors and to understand the binding modes of the known KV10.1 inhibitors. To investigate these binding modes in the central cavity of KV10.1, a unique approach was used that allows derivation and analysis of ligand–protein interactions from molecular dynamics trajectories through pharmacophore modeling. The final molecular dynamics-derived structure-based pharmacophore model for the simulated KV10.1–ligand complexes describes the necessary pharmacophore features for KV10.1 inhibition and is highly similar to the previously reported ligand-based hERG pharmacophore model used to explain the nonselectivity of KV10.1 pore blockers. Moreover, analysis of the molecular dynamics trajectories revealed disruption of the π–π network of aromatic residues F359, Y464, and F468 of KV10.1, which has been reported to be important for binding of various ligands for both KV10.1 and hERG channels. These data indicate that targeting the KV10.1 channel pore is also likely to result in undesired hERG inhibition, and other potential binding sites should be explored to develop true KV10.1-selective inhibitors as new anticancer agents.

Computational methods for unlocking the secrets of potassium channels: Structure, mechanism, and drug design

“…247 a 3D pharmacophore method was constructed and applied to the virtual screening for the voltage-gated K + channel Kv10.1 (Eag1), leading to the identification of the compound ZVS-08 as a voltage-dependent gating inhibitor after structural optimization. 248 Need to be noted, the traditional ligand-based drug design methods such as QSAR and pharmacophore modeling have the inherent limitations. For example, the reliability of built model largely depends on the training data.…”

Diminishing hERG inhibitory activity of aminopiperidine-naphthyridine linked NBTI antibacterials by structural and physicochemical optimizations

“…The screening was done by utilizing an in-house structure-based pharmacophore model substantiated on the voltage-gated potassium channel Kv10.1 (Fig. 1) [40] that shares high sequence similarity with hERG (Kv11.1). Out of 29 NBTIs reported in our previous studies [38,39], the virtual screening yielded 24 hits, with experimental hERG IC 50 values ranging from 0.18 to 13.45 µM (Supporting Information, Table S1).…”

“…1. An aminopiperidine-naphthyridine linked NBTI representative from our previous study [39] comprising 3,5-difluoro-4-bromophenyl RHS embedded into the utilized pharmacophore model for the voltage-gated potassium channel Kv10.1 [40]. The yellow spheres represent hydrophobic interactions, red and green spheres are H-bonding donors and acceptors, respectively, while violet beam-sparkling sphere represents a positive ionazible area.…”

“…Thus docking-derived binding conformations of the newly optimized NBTIs were further subjected to a virtual screening campaign utilizing the aforementioned structure-based pharmacophore model for the voltage-gated potassium channel Kv10.1 [40]. Among 15 optimized NBTI compounds that were screened, the pharmacophore model identified 8 hits as potential hERG blocking agents, whose structural features just partly overlap with the model's pharmacophoric features that represent the hydrophobic interactions (Supporting Information, Table S2).…”