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Pharmacophore Modelling and Virtual Screening for Identification of New Aurora‐A Kinase Inhibitors
Author(s) -
Deng XiaoQiang,
Wang HuiYuan,
Zhao YingLan,
Xiang MingLi,
Jiang PeiDu,
Cao ZhiXing,
Zheng YuZhu,
Luo ShiDong,
Yu LuoTing,
Wei YuQuan,
Yang ShengYong
Publication year - 2008
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2008.00663.x
Subject(s) - pharmacophore , virtual screening , identification (biology) , computational biology , aurora kinase , computer science , chemistry , biology , bioinformatics , biochemistry , botany , cell cycle , cell
Aurora‐A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora‐A inhibitors have been reported recently. In order to clarify the essential structure–activity relationship for the known Aurora‐A inhibitors as well as identify new lead compounds against Aurora‐A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski’s rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF‐7, HepG2 and PC‐3, in which Aurora‐A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.