药效团
虚拟筛选
李宾斯基五定律
烟酰胺磷酸核糖转移酶
生物信息学
化学空间
计算机科学
计算生物学
数量结构-活动关系
化学数据库
化学
药物发现
组合化学
NAD+激酶
立体化学
机器学习
酶
生物化学
生物
有机化学
基因
作者
Qianying Yi,Lu Zhou,Xin Shao,Taijin Wang,Guangkai Bao,Huanhuan Shi,Suwen Zhou,Xiaoli Li,Yahui Tian
出处
期刊:Combinatorial Chemistry & High Throughput Screening
[Bentham Science]
日期:2015-01-08
被引量:2
标识
DOI:10.2174/1386207317666141121124139
摘要
Nicotinamide phosphoribosyltransferase (NAMPT), an enzyme taking part in main NAD biosynthetic pathway, is an attractive target for anticancer therapy. The purpose of our study is to find novel NAMPT inhibitors based on in silico drug discovery means including the generation of 3D-QSAR models, and virtual screening techniques. Firstly, ten pharmacophore models were generated by Catalyst/HypoGen algorithm. Hypo1 with high correl value (0.96), large cost (77.77), and low root mean square deviation (0.81), featured by four chemical features was selected as the best one. Subsequently, Hypo1 was validated through test set prediction and Fischer's randomization methodologies. Then we screened some public compound libraries (Asinex, Ibscreen and Natural products database) using Hypo1 for a 3D query. The screened hits were further refined by Lipinski's rule of five, ADMET properties as well as molecular docking studies. Finally, six molecules with diverse scaffolds exhibited the right pharmacophore features and good binding modes between the receptor and ligands, and were selected as possible candidates against NAMPT for further study.
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