Nagarajan Shanthi, Doddareddy Munikumar reddy, Choo Hyunah, Cho Yong Seo, Oh Kwang-Seok, Lee Byung Ho, Pae Ae Nim
Center for Chemoinformatics Research, Life Sciences Division, Korea Institute of Science and Technology, PO Box 131, Cheongryang, Seoul 130-650, Republic of Korea.
Bioorg Med Chem. 2009 Apr 1;17(7):2759-66. doi: 10.1016/j.bmc.2009.02.041. Epub 2009 Feb 26.
Control of NF-kappaB release through the inhibition of IKKbeta 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 IKKbeta 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 IKKbeta enzyme inhibition test. From the combined approach of virtual screening followed by biological screening, we have identified six novel compounds that can work against IKKbeta, in which 1 compound had highest inhibition rate 82.09% at 10 microM and IC(50) 1.76 microM and 5 compounds had 25.35-48.80% inhibition.
通过抑制IKKβ来控制核因子κB的释放已被确定为治疗炎症性和自身免疫性疾病的一个潜在靶点。我们采用基于结构的虚拟筛选方案从ChemDiv数据库中识别类先导分子。基于四种激酶的晶体结构构建了IKKβ酶的同源模型。该同源模型的有效性已在不同层面得到验证。对接已知抑制剂库揭示了抑制剂可能的结合模式。此外，对接序列分析结果表明Glu172在选择性方面的作用。对ChemDiv数据库进行基于结构的虚拟筛选得到了277个命中结果。挑选并购买了得分最高的75种化合物用于IKKβ酶抑制试验。通过虚拟筛选结合生物筛选的综合方法，我们鉴定出了6种可作用于IKKβ的新型化合物，其中1种化合物在10微摩尔浓度时抑制率最高，为82.09%，半数抑制浓度（IC50）为1.76微摩尔，另外5种化合物的抑制率为25.35% - 48.80%。
