a Molecular Modeling and Drug Design Research Group , School of Health Sciences, University of KwaZulu-Natal , Westville Campus, Durban 4001 , South Africa.
b Pharmaceutical Sciences , University of KwaZulu-Natal , Westville Campus, Durban 4001 , South Africa.
J Biomol Struct Dyn. 2018 Apr;36(5):1118-1133. doi: 10.1080/07391102.2017.1313175. Epub 2017 Apr 17.
The re-emerging Zika virus (ZIKV) is an arthropod-borne virus that has been described to have explosive potential as a worldwide pandemic. The initial transmission of the virus was through a mosquito vector, however, evolving modes of transmission has allowed the spread of the disease over continents. The virus has already been linked to irreversible chronic central nervous system conditions. The concerns of the scientific and clinical community are the consequences of Zika viral mutations, thus suggesting the urgent need for viral inhibitors. There have been large strides in vaccine development against the virus but there are still no FDA approved drugs available. Rapid rational drug design and discovery research is fundamental in the production of potent inhibitors against the virus that will not just mask the virus, but destroy it completely. In silico drug design allows for this prompt screening of potential leads, thus decreasing the consumption of precious time and resources. This study demonstrates an optimized and proven screening technique in the discovery of two potential small molecule inhibitors of ZIKV Methyltransferase and RNA dependent RNA polymerase. This in silico 'per-residue energy decomposition pharmacophore' virtual screening approach will be critical in aiding scientists in the discovery of not only effective inhibitors of Zika viral targets, but also a wide range of anti-viral agents.
重新出现的 Zika 病毒（ZIKV）是一种虫媒病毒，据描述具有在全球范围内引发大流行的巨大潜力。该病毒最初通过蚊子媒介传播，但传播方式的演变使得该疾病在各大洲蔓延。该病毒已经与不可逆的慢性中枢神经系统疾病有关。科学界和临床界关注的是 Zika 病毒突变的后果，因此迫切需要病毒抑制剂。针对该病毒的疫苗开发已经取得了重大进展，但仍没有获得 FDA 批准的药物。快速合理的药物设计和发现研究对于生产强效抑制剂至关重要，这些抑制剂不仅可以掩盖病毒，还可以将其彻底摧毁。计算机药物设计允许对潜在的先导化合物进行快速筛选，从而减少宝贵时间和资源的消耗。本研究展示了一种经过优化和验证的筛选技术，用于发现两种潜在的 Zika 病毒甲基转移酶和 RNA 依赖性 RNA 聚合酶小分子抑制剂。这种计算机“基于残基的能量分解药效团”虚拟筛选方法对于帮助科学家发现不仅对 Zika 病毒靶标有效，而且对广泛的抗病毒药物有效的抑制剂将是至关重要的。
