Investigating Natural Product Inhibitors of IKKα: Insights from Integrative In Silico and Experimental Validation

Nuclear factor-κB (NF-κB) signaling plays a pivotal role in regulating immune responses and is strongly implicated in cancer progression and inflammation-related diseases. The inhibitory κB kinases (IKKs), particularly IKKα, are central to modulating NF-κB activity, with distinct roles in the canoni...

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Main Authors: Muhammad Yasir, Jinyoung Park, Eun-Taek Han, Jin-Hee Han, Won Sun Park, Jongseon Choe, Wanjoo Chun
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Molecules
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Online Access:https://www.mdpi.com/1420-3049/30/9/2025
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Summary:Nuclear factor-κB (NF-κB) signaling plays a pivotal role in regulating immune responses and is strongly implicated in cancer progression and inflammation-related diseases. The inhibitory κB kinases (IKKs), particularly IKKα, are central to modulating NF-κB activity, with distinct roles in the canonical and non-canonical signaling pathways. This study investigates the potential of selectively targeting IKKα to develop novel therapeutic strategies. A receptor–ligand interaction pharmacophore model was generated based on the co-crystallized structure of IKKα, incorporating six key features, two hydrogen bond acceptors, two hydrogen bond donors, one hydrophobic region, and one hydrophobic aromatic region. This model was used to virtually screen a diverse natural compound library of 5540 molecules, yielding 82 candidates that matched the essential pharmacophore features. Molecular docking and molecular dynamics simulations were subsequently employed to evaluate binding conformations, stability, and dynamic behavior of the top hits. The end-state free energy calculations (gmx_MMPBSA) further validated the interaction strength and stability of selected compounds. To experimentally confirm their inhibitory potential, key compounds were tested in LPS-stimulated RAW 264.7 cells, where they significantly reduced IκBα phosphorylation. These findings validate the integrative computational-experimental approach and identify promising natural compounds as selective IKKα inhibitors for further therapeutic development in cancer and inflammatory diseases.
ISSN:1420-3049