Department of Chemistry and Pharmaceutical Chemistry, Faculty of Pharmacy, Al-Azhar University, Gaza, Gaza Strip,
Arch Pharm Res. 2013 Nov;36(11):1326-37. doi: 10.1007/s12272-013-0224-1. Epub 2013 Aug 6.
Dipeptidyl peptidase IV (DPP IV) is an attractive target for the development of new antidiabetic drugs. DPP IV inhibitors improve glycemic control by preventing the rapid inactivation of the incretin hormones; glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide. In the current study, virtual screening, using 2D and 3D filters implemented in a hierarchical cascade, was employed to identify new DPP IV inhibitors. Co-crystallized ligands, with potent DPP IV-inhibitory activities, were utilized to generate structure-based pharmacophore models using DS Visualizer software. The derived pharmacophore maps were validated using in-house built database containing active and inactive DPP IV inhibitors. Subsequently, the optimum validated pharmacophore model was used as a search query against two 3D-databases (NCI and in-house built drug databases). Further hit filtration was carried out employing 2D virtual filters based on Lipinski's rule of 5; number of rotatable bonds and other physicochemical filters. 3D filter using high-throughput molecular docking was also applied. As a result, 5 novel DPP IV inhibitors were discovered as potential lead compounds and later confirmed via in vitro bioassay.
二肽基肽酶 IV（DPP IV）是开发新型抗糖尿病药物的有吸引力的靶标。DPP IV 抑制剂通过防止肠降血糖素激素（胰高血糖素样肽 1（GLP-1）和葡萄糖依赖性胰岛素释放肽）的快速失活来改善血糖控制。在当前的研究中，使用在层次级联中实现的 2D 和 3D 过滤器进行虚拟筛选，以鉴定新的 DPP IV 抑制剂。使用 DS Visualizer 软件，将具有有效 DPP IV 抑制活性的共晶配体用于生成基于结构的药效团模型。使用内部构建的包含活性和非活性 DPP IV 抑制剂的数据库来验证所得药效团图。随后，将优化的验证药效团模型用作针对两个 3D 数据库（NCI 和内部构建的药物数据库）的搜索查询。进一步的命中筛选是基于 Lipinski 的 5 规则、旋转键的数量和其他物理化学过滤条件，使用 2D 虚拟过滤进行的。还应用了使用高通量分子对接的 3D 过滤。结果，发现了 5 种新型 DPP IV 抑制剂作为潜在的先导化合物，并通过体外生物测定进行了进一步确认。
