Department of Biotechnology, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamilnadu, 632014, India.
Appl Biochem Biotechnol. 2019 Jan;187(1):194-210. doi: 10.1007/s12010-018-2814-3. Epub 2018 Jun 18.
The rapid spread of the Zika virus and its association with the abnormal brain development constitute a global health emergency. With a continuing spread of the mosquito vector, the exposure is expected to accelerate in the coming years. Despite number of efforts, there is still no proper vaccine or medicine to combat this virus. Of note, the NS2B-NS3 protein is proven to be the potential target for the Zika virus therapeutics. Hence, e-pharmacophore-based drug design strategy was employed to identify potent inhibitors of NS2B-NS3 protein from ASINEX database consisting of 467,802 molecules. A 3D e-pharmacophore model was generated using PHASE module of Schrödinger Suite. The generated model consists of one hydrogen bond acceptor (A), two hydrogen bond donors (D), and two aromatic rings (R), ADDRR. The model was further evaluated for its ability to screen actives using enrichment analysis. Subsequently, high-throughput virtual screening protocol was employed, and the resultant hit molecules were also examined for its binding free energies and ADME properties using Prime MM-GBSA and Qikprop module of Schrodinger packages, respectively. Finally, the screened hit molecule was subjected to molecular dynamics simulation to examine its stability. Overall, the results from our analysis suggest that compound BAS 19192837 could be a potent inhibitor for the NS2B-NS3 protein of the Zika virus. It is also noteworthy to mention that our results are in good agreement with literature evidences. We hope that this result is of immense importance in designing potential drug molecules to combat the spread of Zika virus in the near future.
寨卡病毒的迅速传播及其与异常大脑发育的关联构成了全球卫生紧急事件。随着蚊子传播媒介的持续传播，预计未来几年暴露率将会加速。尽管已经做出了许多努力，但仍没有针对这种病毒的适当疫苗或药物。值得注意的是，NS2B-NS3 蛋白已被证明是寨卡病毒治疗的潜在靶点。因此，采用基于电子药效团的药物设计策略，从包含 467,802 个分子的 ASINEX 数据库中识别 NS2B-NS3 蛋白的有效抑制剂。使用 Schrödinger Suite 中的 PHASE 模块生成了一个 3D 电子药效团模型。该模型由一个氢键受体 (A)、两个氢键供体 (D) 和两个芳环 (R) 组成，即 ADDRR。该模型进一步通过富集分析评估其筛选活性的能力。随后，采用高通量虚拟筛选方案，并使用 Schrödinger 软件包中的 Prime MM-GBSA 和 Qikprop 模块分别检查所得命中分子的结合自由能和 ADME 性质。最后，对筛选出的命中分子进行分子动力学模拟，以检查其稳定性。总的来说，我们的分析结果表明，化合物 BAS 19192837 可能是寨卡病毒 NS2B-NS3 蛋白的有效抑制剂。值得注意的是，我们的结果与文献证据相符。我们希望这一结果对设计潜在的药物分子以对抗寨卡病毒的传播具有重要意义。
