Novoseletsky V N, Volyntseva A D, Shaitan K V, Kirpichnikov M P, Feofanov A V
M.V.Lomonosov Moscow State University, Faculty of Biology, Leninskie Gory 1, bldg. 12, 119992 , Moscow, Russia.
M.V.Lomonosov Moscow State University, Faculty of Biology, Leninskie Gory 1, bldg. 12, 119992 , Moscow, Russia ; Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Miklukho- Maklaya str. 16/10, 117997, Moscow, Russia.
Acta Naturae. 2016 Apr-Jun;8(2):35-46.
Modeling of the structure of voltage-gated potassium (KV) channels bound to peptide blockers aims to identify the key amino acid residues dictating affinity and provide insights into the toxin-channel interface. Computational approaches open up possibilities for in silico rational design of selective blockers, new molecular tools to study the cellular distribution and functional roles of potassium channels. It is anticipated that optimized blockers will advance the development of drugs that reduce over activation of potassium channels and attenuate the associated malfunction. Starting with an overview of the recent advances in computational simulation strategies to predict the bound state orientations of peptide pore blockers relative to KV-channels, we go on to review algorithms for the analysis of intermolecular interactions, and then take a look at the results of their application.
对与肽类阻滞剂结合的电压门控钾（KV）通道结构进行建模，旨在确定决定亲和力的关键氨基酸残基，并深入了解毒素-通道界面。计算方法为选择性阻滞剂的计算机辅助合理设计开辟了可能性，这些新的分子工具可用于研究钾通道的细胞分布和功能作用。预计优化后的阻滞剂将推动减少钾通道过度激活并减轻相关功能障碍的药物的开发。我们首先概述了预测肽类孔道阻滞剂相对于KV通道的结合态取向的计算模拟策略的最新进展，接着回顾了分子间相互作用分析算法，然后看看它们的应用结果。
