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利用高通量筛选平台鉴定新型NaV1.7拮抗剂。

Identification of novel NaV1.7 antagonists using high throughput screening platforms.

作者信息

Klement Goran, Babich Olga, Larsson Olof, Lund Per-Eric, Malmberg Asa, Sandberg Lars, Sands Zara A, Dabrowski Michael

机构信息

AstraZeneca R&D, CNSP iMed, Sodertalje, Sweden.

出版信息

Comb Chem High Throughput Screen. 2012 Nov;15(9):713-20. doi: 10.2174/138620712803519680.

Abstract

Congenital Insensitivity to Pain (CIP) is a loss of function mutation resulting in a truncated NaV1.7 protein, suggesting a pivotal role in pain signaling and rendering it an important pharmaceutical target for multiple pain conditions. The structural homology in the NaV-channel family makes it challenging to design effective analgesic compounds without inducing for example cardiotoxicity or seizure liabilities. An additional approach to structural isoform selectivity is to identify compounds with use- or state-dependent profiles, i.e. inhibition efficacy based on the gating of the ion channel. In general nerve cells in damaged or inflamed tissue are more depolarized and electrically active compared to healthy nerve cells in for instance the heart. This observation has led to the design of two types of screening protocols emulating the voltage condition of peripheral neurons or cardiac tissue. The two voltage protocols have been developed to identify both use- and state-dependent antagonists. In this paper we describe an attempt to merge the two different protocols into one to increase screening efficacy, while retaining relevant state- and use-dependent pharmacology. The new protocol is constructed of two stimulation pulses and a slow voltage ramp for simultaneous assessment of resting and state-dependent block. By comparing all protocols we show that the new protocol indeed filter compounds for state-dependence and increase the prediction power of selecting use-dependent compounds.

摘要

先天性无痛觉(CIP)是一种功能丧失性突变,导致截短的NaV1.7蛋白,这表明其在疼痛信号传导中起关键作用,并使其成为多种疼痛病症的重要药物靶点。NaV通道家族中的结构同源性使得设计有效的镇痛化合物具有挑战性,因为这可能会引发例如心脏毒性或癫痫发作等不良反应。另一种实现结构亚型选择性的方法是鉴定具有使用或状态依赖性特征的化合物,即基于离子通道门控的抑制效力。一般来说,与例如心脏中的健康神经细胞相比,受损或发炎组织中的神经细胞去极化程度更高且电活性更强。这一观察结果导致设计了两种模拟外周神经元或心脏组织电压条件的筛选方案。这两种电压方案已被开发用于鉴定使用依赖性和状态依赖性拮抗剂。在本文中,我们描述了一种将两种不同方案合并为一种以提高筛选效率的尝试,同时保留相关的状态依赖性和使用依赖性药理学特性。新方案由两个刺激脉冲和一个缓慢的电压斜坡组成,用于同时评估静息和状态依赖性阻滞。通过比较所有方案,我们表明新方案确实能够筛选出具有状态依赖性的化合物,并提高选择使用依赖性化合物的预测能力。

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