Ma Biao, Yamaguchi Keiichi, Fukuoka Mayuko, Kuwata Kazuo
United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan.
United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan; Department of Gene and Development, Graduate School of Medicine, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan.
Biochem Biophys Res Commun. 2016 Jan 22;469(4):930-5. doi: 10.1016/j.bbrc.2015.12.106. Epub 2015 Dec 24.
To accelerate the logical drug design procedure, we created the program "NAGARA," a plugin for PyMOL, and applied it to the discovery of small compounds called medical chaperones (MCs) that stabilize the cellular form of a prion protein (PrP(C)). In NAGARA, we constructed a single platform to unify the docking simulation (DS), free energy calculation by molecular dynamics (MD) simulation, and interfragment interaction energy (IFIE) calculation by quantum chemistry (QC) calculation. NAGARA also enables large-scale parallel computing via a convenient graphical user interface. Here, we demonstrated its performance and its broad applicability from drug discovery to lead optimization with full compatibility with various experimental methods including Western blotting (WB) analysis, surface plasmon resonance (SPR), and nuclear magnetic resonance (NMR) measurements. Combining DS and WB, we discovered anti-prion activities for two compounds and tegobuvir (TGV), a non-nucleoside non-structural protein NS5B polymerase inhibitor showing activity against hepatitis C virus genotype 1. Binding profiles predicted by MD and QC are consistent with those obtained by SPR and NMR. Free energy analyses showed that these compounds stabilize the PrP(C) conformation by decreasing the conformational fluctuation of the PrP(C). Because TGV has been already approved as a medicine, its extension to prion diseases is straightforward. Finally, we evaluated the affinities of the fragmented regions of TGV using QC and found a clue for its further optimization. By repeating WB, MD, and QC recursively, we were able to obtain the optimum lead structure.
为了加速合理的药物设计过程，我们创建了“NAGARA”程序，它是PyMOL的一个插件，并将其应用于发现称为医学伴侣分子（MCs）的小分子化合物，这些化合物可稳定朊病毒蛋白（PrP(C)）的细胞形式。在NAGARA中，我们构建了一个单一平台，以统一对接模拟（DS）、通过分子动力学（MD）模拟进行的自由能计算以及通过量子化学（QC）计算进行的片段间相互作用能（IFIE）计算。NAGARA还通过便捷的图形用户界面实现大规模并行计算。在此，我们展示了其性能以及从药物发现到先导优化的广泛适用性，它与包括蛋白质印迹（WB）分析、表面等离子体共振（SPR）和核磁共振（NMR）测量在内的各种实验方法完全兼容。结合DS和WB，我们发现了两种化合物以及替诺福韦酯（TGV）的抗朊病毒活性，TGV是一种对丙型肝炎病毒1型有活性的非核苷非结构蛋白NS5B聚合酶抑制剂。由MD和QC预测的结合谱与通过SPR和NMR获得的谱一致。自由能分析表明，这些化合物通过减少PrP(C)的构象波动来稳定PrP(C)构象。由于TGV已被批准作为一种药物，将其扩展用于朊病毒疾病很直接。最后，我们使用QC评估了TGV片段区域的亲和力，并找到了进一步优化的线索。通过递归地重复WB、MD和QC，我们能够获得最佳的先导结构。
