Cheng Li Ping, Wang Tian Chi, Yu Rao, Li Meng, Huang Jin Wen
School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai 201418, China.
School of Chemical and Environmental Engineering, Shanghai Institute of Technology, Shanghai 201418, China.
Bioorg Med Chem Lett. 2018 Dec 15;28(23-24):3622-3629. doi: 10.1016/j.bmcl.2018.10.040. Epub 2018 Oct 26.
Neuraminidase (NA) is an important antiviral drug target. Zanamivir is one of the most potent NA inhibitors. In this paper, a series of zanamivir derivatives as potential NA inhibitors were studied by combination of molecular modeling techniques including 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation. The results show that the best CoMFA (comparative molecular field analysis) model has q = 0.728 and r = 0.988, and the best CoMSIA (comparative molecular similarity indices analysis) model has q = 0.750 and r = 0.981, respectively. The built 3D-QSAR models show significant statistical quality and excellent predictive ability. Seven new NA inhibitors were designed and predicted. 20 ns of MD simulations were carried out and their binding free energies were calculated. Two designed compounds were selected to be synthesized and biologically evaluated by NA inhibition and virus inhibition assays. One compound (IC = 0.670 µM, SI > 149) exhibits excellent antiviral activity against A/WSN/33 H1N1, which is superior to the reference drug zanamivir (IC = 0.873 µM, SI > 115). The theoretical and experimental results may provide reference for development of new anti-influenza drugs.
神经氨酸酶（NA）是一个重要的抗病毒药物靶点。扎那米韦是最有效的NA抑制剂之一。本文通过结合三维定量构效关系（3D-QSAR）、分子对接和分子动力学（MD）模拟等分子建模技术，研究了一系列作为潜在NA抑制剂的扎那米韦衍生物。结果表明，最佳的比较分子场分析（CoMFA）模型的q值为0.728，r值为0.988，而最佳的比较分子相似性指数分析（CoMSIA）模型的q值为0.750，r值为0.981。所构建的3D-QSAR模型显示出显著的统计学质量和出色的预测能力。设计并预测了7种新型NA抑制剂。进行了20纳秒的MD模拟，并计算了它们的结合自由能。选择两种设计的化合物进行合成，并通过NA抑制和病毒抑制试验进行生物学评估。一种化合物（IC = 0.670 μM，SI > 149）对A/WSN/33 H1N1表现出优异的抗病毒活性，优于参考药物扎那米韦（IC = 0.873 μM，SI > 115）。理论和实验结果可为新型抗流感药物的开发提供参考。
