Yasir Muhammad, Park Jinyoung, Han Eun-Taek, Han Jin-Hee, Park Won Sun, Choe Jongseon, Chun Wanjoo
Department of Pharmacology, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea.
Department of Medical Environmental Biology and Tropical Medicine, Kangwon National University School of Medicine, Chuncheon 24341, Republic of Korea.
Molecules. 2025 May 2;30(9):2025. doi: 10.3390/molecules30092025.
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.
核因子-κB(NF-κB)信号传导在调节免疫反应中起关键作用,并且与癌症进展和炎症相关疾病密切相关。抑制性κB激酶(IKK),特别是IKKα,对于调节NF-κB活性至关重要,在经典和非经典信号通路中具有不同作用。本研究调查了选择性靶向IKKα以开发新治疗策略的潜力。基于IKKα的共结晶结构生成了一个受体-配体相互作用药效团模型,该模型包含六个关键特征,两个氢键受体、两个氢键供体、一个疏水区域和一个疏水芳香区域。该模型用于虚拟筛选一个包含5540个分子的多样化天然化合物库,产生了82个符合基本药效团特征的候选物。随后采用分子对接和分子动力学模拟来评估顶级命中物的结合构象、稳定性和动态行为。终态自由能计算(gmx_MMPBSA)进一步验证了所选化合物的相互作用强度和稳定性。为了通过实验证实它们的抑制潜力,在脂多糖刺激的RAW 264.7细胞中测试了关键化合物,它们在这些细胞中显著降低了IκBα磷酸化。这些发现验证了综合计算-实验方法,并确定了有前景的天然化合物作为选择性IKKα抑制剂,用于癌症和炎症性疾病的进一步治疗开发。