Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan.
Curr Top Med Chem. 2013;13(9):989-1001. doi: 10.2174/1568026611313090003.
Protein:protein interactions are becoming increasingly significant as potential drug targets; however, the rational identification of small molecule inhibitors of such interactions remains a challenge. Pharmacophore modelling is a popular tool for virtual screening of compound libraries, and has previously been successfully applied to the discovery of enzymatic inhibitors. However, the application of pharmacophore modelling in the field of protein:protein interaction inhibitors has historically been considered more of a challenge and remains limited. In this review, we explore the interaction mimicry by known inhibitors that originate from in vitro screening, demonstrating the validity of pharmacophore mapping in the generation of queries for virtual screening. We discuss the pharmacophore mapping methods that have been successfully employed in the discovery of first-in-class inhibitors. These successful cases demonstrate the usefulness of a "tool kit" of diverse strategies for application across a range of situations depending on the available structural information.
蛋白质-蛋白质相互作用作为潜在的药物靶点变得越来越重要;然而,合理识别此类相互作用的小分子抑制剂仍然是一个挑战。药效团模型是化合物库虚拟筛选的常用工具,以前已成功应用于酶抑制剂的发现。然而,药效团模型在蛋白质-蛋白质相互作用抑制剂领域的应用历来被认为更具挑战性,并且仍然受到限制。在这篇综述中,我们探讨了来自体外筛选的已知抑制剂的相互作用模拟,证明了药效团映射在虚拟筛选中生成查询的有效性。我们讨论了已成功应用于发现首创类抑制剂的药效团映射方法。这些成功案例证明了“工具包”中各种策略的有用性,可根据可用的结构信息在各种情况下应用。