What is it about?
Inhibitor kappa‐B kinase‐beta (IKK‐β) controls the activation of nuclear transcription factor kappa‐B and has been linked to inflammation and cancer. Therefore, inhibitors of this kinase should have potent anti‐inflammatory and anticancer properties. Accordingly, we explored the pharmacophoric space of 218 IKK‐β inhibitors to identify high‐quality binding models. Subsequently , genetic algorithm‐based QSAR Q2 analysis was employed to select the best possible combination of pharmacophoric models and physicochemical descriptors that explain bioactivity variation among training compounds. Three successful pharmacophores emerged in 2 optimal QSAR equations (r12175 = 0.733, r12LOO = 0.52, F1 = 65.62, r12PRESS against 43 test inhibi-tors = 0.63 and r22175 = 0.683, r22LOO = 0.52, F2 = 72.66, r22PRESS against 43 test inhibi-tors = 0.65). Two pharmacophores were merged in a single binding model. Receiver operating characteristic curve validation proved the excellent qualities of this model. The merged pharmacophore and the associated QSAR equations were applied to screen the National Cancer Institute list of compounds. Ten hits were found to exhibit potent anti‐IKK‐β bioactivity, out of which, one illustrates IC50 of 11.0nM
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Why is it important?
It is a hot target for treatment of cancer
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This page is a summary of: Discovery of novel potent nuclear factor kappa-B inhibitors (IKK-β) via extensive ligand-based modeling and virtual screening, Journal of Molecular Recognition, December 2016, Wiley,
DOI: 10.1002/jmr.2604.
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