IKKβ inhibitors identification part I: Homology model assisted structure based virtual screening

被引:31
作者
Nagarajan, Shanthi [1 ,2 ]
Doddareddy, Munikumar Reddy [1 ,2 ]
Choo, Hyunah [1 ]
Cho, Yong Seo [1 ]
Oh, Kwang-Seok [3 ]
Lee, Byung Ho [3 ]
Pae, Ae Nim [1 ]
机构
[1] Korea Inst Sci & Technol, Div Life Sci, Ctr Chemoinformat Res, Seoul 130650, South Korea
[2] Korea Univ Sci & Technol, Sch Sci, Taejon 305333, South Korea
[3] Korea Res Inst Chem Technol, Drug Discovery Div, Taejon 305606, South Korea
关键词
IKK; IKK beta; Inhibitor kappa B kinase; Homology modeling; Virtual screening; Docking; Flex-X; Pharmacophore constraints; Enrichment; KAPPA-B KINASE; HIGHLY SELECTIVE INHIBITOR; HIT-TO-LEAD; POTENT; ACTIVATION; INFLAMMATION; DERIVATIVES; BMS-345541; GENERATION; STRATEGIES;
D O I
10.1016/j.bmc.2009.02.041
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Control of NF-kappa B release through the inhibition of IKK beta has been identified as a potential target for the treatment of inflammatory and autoimmune diseases. We have employed structure based virtual screening scheme to identify lead like molecule from ChemDiv database. Homology models of IKK beta enzyme were developed based on the crystal structures of four kinases. The efficiency of the homology model has been validated at different levels. Docking of known inhibitors library revealed the possible binding mode of inhibitors. Besides, the docking sequence analyses results indicate the responsibility of Glu172 in selectivity. Structure based virtual screening of ChemDiv database has yielded 277 hits. Top scoring 75 compounds were selected and purchased for the IKK beta enzyme inhibition test. From the combined approach of virtual screening followed by biological screening, we have identified six novel compounds that can work against IKK beta, in which 1 compound had highest inhibition rate 82.09% at 10 mu M and IC50 1.76 mu M and 5 compounds had 25.35-48.80% inhibition. (c) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2759 / 2766
页数:8
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