Division of Medicinal Chemistry, College of Pharmacy, The University of Texas at Austin , Austin, Texas 78712, United States.
J Chem Inf Model. 2014 May 27;54(5):1467-75. doi: 10.1021/ci500114r. Epub 2014 May 5.
PERK, as one of the principle unfolded protein response signal transducers, is believed to be associated with many human diseases, such as cancer and type-II diabetes. There has been increasing effort to discover potent PERK inhibitors due to its potential therapeutic interest. In this study, a computer-based virtual screening approach is employed to discover novel PERK inhibitors, followed by experimental validation. Using a focused library, we show that a consensus approach, combining pharmacophore modeling and docking, can be more cost-effective than using either approach alone. It is also demonstrated that the conformational flexibility near the active site is an important consideration in structure-based docking and can be addressed by using molecular dynamics. The consensus approach has further been applied to screen the ZINC lead-like database, resulting in the identification of 10 active compounds, two of which show IC50 values that are less than 10 μM in a dose-response assay.
PERK(一种未折叠蛋白反应信号转导途径中的关键蛋白)被认为与许多人类疾病相关,如癌症和 II 型糖尿病。由于其潜在的治疗意义,人们越来越努力地发现有效的 PERK 抑制剂。在这项研究中,我们采用了基于计算机的虚拟筛选方法来发现新型的 PERK 抑制剂,随后进行了实验验证。使用一个有针对性的文库,我们表明,结合药效基团建模和对接的共识方法比单独使用任何一种方法都更具成本效益。此外,还证明了活性位点附近的构象灵活性是基于结构对接的一个重要考虑因素,并且可以通过使用分子动力学来解决。共识方法进一步应用于筛选 ZINC 类药性数据库,鉴定出 10 种活性化合物,其中两种在剂量反应测定中显示出的 IC50 值小于 10μM。