IKK beta inhibitor identification: a multi-filter driven novel scaffold

Abstract

Background: Nuclear factor kappa B (NF-kappa B) is a chief nuclear transcription factor that controls the transcription of various genes; and its activation is tightly controlled by Inhibitor kappa B kinase (IKK). The irregular transcription of NF-kappa B has been linked to auto-immune disorders, cancer and other diseases. The IKK complex is composed of three units, IKK alpha, IKK beta, and the regulatory domain NEMO, of which IKK beta is well understood in the canonical pathway. Therefore, the inhibition of IKK beta by drugs forms the molecular basis for anti-inflammatory drug research. Results: The ligand-and structure-based virtual screening (VS) technique has been applied to identify IKK beta inhibitors from the ChemDiv database with 0.7 million compounds. Initially, a 3D-QSAR pharmacophore model has been deployed to greatly reduce the database size. Subsequently, recursive partitioning (RP) and docking filters were used to screen the pharmacophore hits. Finally, 29 compounds were selected for IKK beta enzyme inhibition assay to identify a novel small molecule inhibitor of IKK beta protein. Conclusions: In the present investigation, we have applied various computational models sequentially to virtually screen the ChemDiv database, and identified a small molecule that has an IC50 value of 20.3 mu M. This compound is novel among the known IKK beta inhibitors. Further optimization of the hit compound can reveal a more potent anti-inflammatory agent.