Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University Vienna, Spitalgasse 4, 1090, Vienna, Austria.
Biovista, 34 Rodopoleos Street, 16777, Athens, Greece.
Cell Biol Toxicol. 2023 Dec;39(6):2793-2819. doi: 10.1007/s10565-023-09803-y. Epub 2023 Apr 24.
GABA receptors, members of the pentameric ligand-gated ion channel superfamily, are widely expressed in the central nervous system and mediate a broad range of pharmaco-toxicological effects including bidirectional changes to seizure threshold. Thus, detection of GABA receptor-mediated seizure liabilities is a big, partly unmet need in early preclinical drug development. This is in part due to the plethora of allosteric binding sites that are present on different subtypes of GABA receptors and the critical lack of screening methods that detect interactions with any of these sites. To improve in silico screening methods, we assembled an inventory of allosteric binding sites based on structural data. Pharmacophore models representing several of the binding sites were constructed. These models from the NeuroDeRisk IL Profiler were used for in silico screening of a compiled collection of drugs with known GABA receptor interactions to generate testable hypotheses. Amoxapine was one of the hits identified and subjected to an array of in vitro assays to examine molecular and cellular effects on neuronal excitability and in vivo locomotor pattern changes in zebrafish larvae. An additional level of analysis for our compound collection is provided by pharmacovigilance alerts using FAERS data. Inspired by the Adverse Outcome Pathway framework, we postulate several candidate pathways leading from specific binding sites to acute seizure induction. The whole workflow can be utilized for any compound collection and should inform about GABA receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.
GABA 受体是五聚体配体门控离子通道超家族的成员,广泛表达于中枢神经系统,介导广泛的药物毒性作用,包括对癫痫发作阈值的双向改变。因此,检测 GABA 受体介导的癫痫发作倾向是早期临床前药物开发中的一个重大但尚未得到满足的需求。部分原因是不同 GABA 受体亚型上存在大量的变构结合位点,而缺乏能够检测到与这些位点中任何一个结合的筛选方法。为了改进基于计算机的筛选方法,我们根据结构数据构建了一个变构结合位点清单。构建了代表几个结合位点的药效团模型。这些来自 NeuroDeRisk IL Profiler 的模型被用于对具有已知 GABA 受体相互作用的已编译药物集合进行基于计算机的筛选,以生成可测试的假说。阿莫沙平是鉴定出的命中之一,并进行了一系列体外测定,以检查对神经元兴奋性的分子和细胞影响,以及斑马鱼幼虫的体内运动模式变化。使用 FAERS 数据进行药物警戒警报为我们的化合物集合提供了额外的分析水平。受不良结局途径框架的启发,我们提出了从特定结合位点到急性癫痫发作诱导的几个候选途径。与主要基于功能数据的标准置换筛选相比,整个工作流程可用于任何化合物集合,并且应该更全面地了解 GABA 受体介导的癫痫发作风险。