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PubMed · 17201412

Discovering potassium channel blockers from synthetic compound database by using structure-based virtual screening in conjunction with electrophysiological assay.

Abstract

Potassium ion (K+) channels are attractive targets for drug discovery because of the essential roles played in biological systems. However, high-throughput screening (HTS) cannot be used to screen K+ channel blockers. To overcome this disadvantage of HTS, we have developed a virtual screening approach for discovering novel blockers of K+ channels. On the basis of a three-dimensional model of the eukaryotic K+ channels, molecular docking-based virtual screening was employed to search the chemical database MDL Available Chemicals Directory (ACD). Compounds were ranked according to their relative binding energy, favorable shape complementarity, and potential to form hydrogen bonds with the outer mouth of the K+ channel model. Twenty candidate compounds selected from the virtual screening were examined using the whole-cell voltage-clamp recording in rat dissociated hippocampal neurons. Among them, six compounds (5, 6, 8, 18-20) potently blocked both the delayed rectifier (IK) and fast transient K+ currents (IA). When applied externally, these six compounds preferentially blocked IK with potencies 2- to 500-fold higher than that of tetraethylammonium chloride. Intracellular application of the six compounds had no effect on both K+ currents. In addition, the interaction models and binding free energy calculations demonstrated that hydrophobic interaction and solvent effects play important roles in the inhibitory activities of these compounds. The results demonstrated that structure-based computer screening strategy could be used to identify novel, structurally diverse compounds targeting the pore binding pocket of the outer mouth of voltage-gated K+ channels. This study provides an alternative way of finding new blockers of voltage-gated K+ channels, while the techniques for high-throughput screening of K+ channel drugs remain in development.

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BibTeXRIS

Hong Liu, Zhao-Bing Gao, Zhiyi Yao, Suxin Zheng, Yang Li, Weiliang Zhu, Xiaojian Tan, Xiaomin Luo, Jianhua Shen, Kaixian Chen, Guo-Yuan Hu, Hualiang Jiang. 2007-01-11. Discovering potassium channel blockers from synthetic compound database by using structure-based virtual screening in conjunction with electrophysiological assay.. https://doi.org/10.1021/jm060414o

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