Pirard Bernard, Brendel Joachim, Peukert Stefan
Aventis Pharma Deutschland GmbH, A Company of the Sanofi-Aventis Group, Computational Chemistry, Medicinal Chemistry, Industrie Park Höchst, Building G878, D-65926 Frankfurt am Main, Germany.
J Chem Inf Model. 2005 Mar-Apr;45(2):477-85. doi: 10.1021/ci0400011.
Different virtual screening techniques are available as alternatives to high throughput screening. These different techniques have been rarely used together on the same target. We had the opportunity to do so in order to discover novel blockers of the voltage-dependent potassium channel Kv1.5, a potential target for the treatment of atrial fibrillation. Our corporate database was searched, using a protein-based pharmacophore, derived from a homology model, as query. As a result, 244 molecules were screened in vitro, 19 of them (7.8%) were found to be active. Five of them, belonging to five different chemical classes, exhibited IC50 values under 10 microM. The performance of this structure-based virtual screening protocol has been compared with those of similarity and ligand-based pharmacophore searches. The analysis of the results supports the conventional wisdom of using as many virtual screening techniques as possible in order to maximize the chance of finding as many chemotypes as possible.
不同的虚拟筛选技术可作为高通量筛选的替代方法。这些不同的技术很少在同一靶点上一起使用。我们有机会这样做,以发现电压依赖性钾通道Kv1.5的新型阻滞剂,Kv1.5是治疗心房颤动的一个潜在靶点。我们使用基于同源模型衍生的基于蛋白质的药效团作为查询,搜索了公司数据库。结果,体外筛选了244个分子,其中19个(7.8%)被发现具有活性。其中五个属于五个不同的化学类别,其IC50值低于10 microM。已将这种基于结构的虚拟筛选方案的性能与基于相似性和配体的药效团搜索的性能进行了比较。结果分析支持了尽可能使用多种虚拟筛选技术以最大化发现尽可能多化学类型机会的传统观点。