Academic Journals Database
Disseminating quality controlled scientific knowledge

IKKβ inhibitor identification: a multi-filter driven novel scaffold

ADD TO MY LIST
 
Author(s): Nagarajan Shanthi | Choo Hyunah | Cho Yong | Shin Kye Jung | Oh Kwang-Seok | Lee Byung | Pae Ae

Journal: BMC Bioinformatics
ISSN 1471-2105

Volume: 11;
Issue: Suppl 7;
Start page: S15;
Date: 2010;
VIEW PDF   PDF DOWNLOAD PDF   Download PDF Original page

ABSTRACT
Abstract Background Nuclear factor kappa B (NF-κB) 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-κB has been linked to auto-immune disorders, cancer and other diseases. The IKK complex is composed of three units, IKKα, IKKβ, and the regulatory domain NEMO, of which IKKβ is well understood in the canonical pathway. Therefore, the inhibition of IKKβ 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 IKKβ 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 IKKβ enzyme inhibition assay to identify a novel small molecule inhibitor of IKKβ 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 20.3μM. This compound is novel among the known IKKβ inhibitors. Further optimization of the hit compound can reveal a more potent anti-inflammatory agent.

Tango Rapperswil
Tango Rapperswil

     Save time & money - Smart Internet Solutions