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As an important transcription factor of the
Ral family, nuclear factor-kappa B (NF-κB) is involved in numerous cellular processes, such as the responses to cellular stress and to inflammation. For better elucidating the quantitative structure–activity relationship of NF-κB inhibitors and determining possible ligand–protein interaction, a pharmacophore model, Hypo1, was built based on 35 training molecules by Catalyst/HypoGen algorithm. The five pharmacophore features of Hypo1, including three hydrophobic groups, one hydrogen-bond acceptor, and one hydrophobic aromatic group, were correctly mapped onto NF-κB surface. This model has strong capability to identify NF-κB inhibitors and to predict the activities of structurally diverse molecules, thus to provide a valuable tool in the design of new leads with desired biological activity by virtual screening.
Pharmacophore features and a docking conformation are correctly matched onto NF-κB surface.