Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics.
Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics.
复制标题
DOI：
10.3390/biotech10010001
复制
发表时间：
2020-12-28
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
登革热是由登革热病毒（DENV）引起的疾病，是世界上许多热带和亚热带地区尚未解决的主要问题。由于缺乏有效防止病毒在人体内进一步传播的治疗，每年全球死亡人数很高。因此，需要新的抗登革热疗法来进行有效治疗。人己糖激酶II（HKII）是糖酵解途径中的第一个酶，由于其对宿主细胞中病毒复制和存活的显著影响而成为重要的药物靶标。在这项研究中，使用超快形状识别与CREDO原子类型（USRCAT）算法对HKII进行了2310万种化合物的计算筛选。总共有300种化合物与三种参考分子（称为α-D-葡萄糖（GLC），β-D-葡萄糖-6-磷酸（BG6）和2-脱氧葡萄糖（2DG））具有最高的相似性评分。在这300种化合物中，选择了165种化合物进行进一步的基于结构的筛选，基于它们的相似性评分、ADME分析、Lipinski的五分法则和虚拟毒性测试结果。随后使用AutoDock维纳程序将选择的类似物对接到HKII结构的每个结构域（PDB ID：2NZT）。然后根据结合能、形成的氢键数量和特定的催化残基从对接结果中选择每个查询的三个排名最高的化合物。在链B的C-末端观察到每种类似物的最佳对接结果。GLC的顶级类似物，化合物10，化合物26和化合物58，分别显示预测的结合能为− 7.2，− 7.0和− 6.10 kcal/mol以及7，5和2个氢键。BG 6的类似物、化合物30、化合物36和化合物38显示出预测的结合能为-7.8、-7.4和-7.0千卡/摩尔，以及11、9和5个氢键，而2DG的前三个类似物，称为化合物1、化合物4和化合物31，显示出预测的结合能为-6.8、-6.3、-6.4和-6.3。和-6.3千卡/摩尔和4，3，和1氢键，依次。然后选择对接分析中排名最高的化合物进行分子动力学模拟，其中化合物10、化合物30和化合物1（其为GLC、BG 6和2DG的类似物）已经显示出强的蛋白质-配体稳定性，其中RMSD值分别为5H键± 5.0 A °、8H键± 4.0 A °和2H键± 0.5 A °，在整个20 ns模拟时间内与参考分子进行比较。因此，通过使用计算研究，我们提出了新的化合物，这可能是潜在的药物，通过抑制HKII的活性，对DENV。
Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Human hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Alpha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we proposed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity.
登录
查看更多内容
DOI：
10.3390/ijerph10126319
发表时间：
2013-11-26
影响因子：
--
作者：
Cheong YL;Burkart K;Leitão PJ;Lakes T
通讯作者：
Lakes T
DOI：
10.1080/14756366.2017.1306521
发表时间：
2017-12
影响因子：
5.6
作者：
Kouretova J;Hammamy MZ;Epp A;Hardes K;Kallis S;Zhang L;Hilgenfeld R;Bartenschlager R;Steinmetzer T
通讯作者：
Steinmetzer T
影响因子：
3.7
作者：
de Almeida H;Bastos IM;Ribeiro BM;Maigret B;Santana JM
通讯作者：
Santana JM
影响因子：
4.2
作者：
Behnam, Mira A. M.;Nitsche, Christoph;Klein, Christian D.
通讯作者：
Klein, Christian D.
影响因子：
4.9
作者：
Byrd, Chelsea M.;Dai, Dongcheng;Jordan, Robert
通讯作者：
Jordan, Robert