Onawole Abdulmujeeb T, Sulaiman Kazeem O, Adegoke Rukayat O, Kolapo Temitope U
Department of Chemistry, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
Department of Chemistry, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia.
J Mol Graph Model. 2017 May;73:54-61. doi: 10.1016/j.jmgm.2017.01.018. Epub 2017 Feb 9.
The Zika virus (ZIKV) is a life threatening pathogen of zoonotic importance with prevalence in some parts of Africa and America. Unfortunately, there is yet to be a single approved vaccine or antiviral drug to treat the diseases and deformations being caused by the Zika virus infection. In this study, about 36 million compounds from MCULE database were virtually screened against a real matured ZIKV protein using a consensus scoring method to get improved hit rates. The consensus scoring method combined the result from the 25 top ranked molecules from both MCULE and Drug Score eXtended (DSX) docking programs which led to the selection of two hit compounds. The inhibition constant (Ki) values of 0.08 and 0.30μm were obtained for the two selected compounds MCULE-8830369631-0-1 and MCULE-9236850811-0-1 respectively, to remark them as hit compounds. The molecular interactions of the two selected hit compounds with the amino acids (ALA 48, ILE 49, ILE 468 and LEU 472) present in the ZIKV protein indicated that they both have similar binding modes. The result of the computationally predicted physicochemical properties including ADMET for the selected compounds showed their great potential in becoming lead compounds upon optimization and thus could be used in treating the Zika virus diseases.
寨卡病毒（ZIKV）是一种具有人畜共患病重要性的威胁生命的病原体，在非洲和美洲的一些地区流行。不幸的是，目前尚无单一获批的疫苗或抗病毒药物来治疗由寨卡病毒感染引起的疾病和畸形。在本研究中，使用共识评分方法对来自MCULE数据库的约3600万种化合物进行了虚拟筛选，以针对真实成熟的寨卡病毒蛋白提高命中率。共识评分方法结合了来自MCULE和药物评分扩展（DSX）对接程序的25种排名靠前的分子的结果，从而选择了两种命中化合物。分别为两种选定的化合物MCULE-8830369631-0-1和MCULE-9236850811-0-1获得了0.08和0.30μm的抑制常数（Ki）值，将它们标记为命中化合物。两种选定的命中化合物与寨卡病毒蛋白中存在的氨基酸（ALA 48、ILE 49、ILE 468和LEU 472）的分子相互作用表明它们具有相似的结合模式。对选定化合物的包括ADMET在内的计算预测物理化学性质的结果表明，它们在优化后具有成为先导化合物的巨大潜力，因此可用于治疗寨卡病毒疾病。
