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

Control of NF-κB release through the inhibition of IKKβ 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 IKKβ 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 IKKβ enzyme inhibition test. From the combined approach of virtual screening followed by biological screening, we have identified six novel compounds that can work against IKKβ, in which 1 compound had highest inhibition rate 82.09% at 10 μM and IC 50 1.76 μM and 5 compounds had 25.35–48.80% inhibition.