IKKβ inhibitor identification: a multi-filter driven novel scaffold

Title
IKKβ inhibitor identification: a multi-filter driven novel scaffold
Authors
샨티추현아조용서신계정오광석이병호배애님
Keywords
IKKβ; Reumatis Arthritis; virtual screening
Issue Date
2010-10
Publisher
BMC bioinformatics. [electronic resource]
Citation
VOL 11, S15-1-S15-10
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 antiinflammatory agent.
URI
http://pubs.kist.re.kr/handle/201004/41313
ISSN
1471-2105
Appears in Collections:
KIST Publication > Article
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