Department of Bio & Medical Big Data (BK4 Program), Division of Life Science, Research Institute of Natural Science (RINS), Gyeongsang National University (GNU), 501 Jinju-daero, Jinju 52828, Republic of Korea.
ANGEL i-Drug Design (AiDD), Jinju 52828, Republic of Korea.
Biomolecules. 2023 Jan 22;13(2):217. doi: 10.3390/biom13020217.
Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed.
In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb's free energy landscape.
Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.
激活的 Cdc42 相关激酶(ACK1)对于许多细胞功能至关重要,例如生长、增殖和迁移。ACK1 信号通过多种受体酪氨酸激酶发生;因此,其抑制作用可以对多种人类癌症产生有效的抗增殖作用。在过去十年中,设计并发现了许多 ACK1 特异性抑制剂,但没有一种进入临床阶段。迫切需要有效的、选择性的 ACK1 抑制剂。
在本研究中,利用两个不同的与 ACK1 晶体结构偶联的抑制剂,合理构建了药效团模型(PM)。利用生成的 PM 对来自四个化学数据库的药物样数据库进行筛选。利用分子对接(MD)研究预测药效团映射化合物的结合模式。将 MD 中筛选出的命中蛋白复合物在全原子分子动力学模拟(MDS)中进行 500 ns 的研究。使用结合自由能计算(ΔG kJ/mol)和吉布斯自由能景观对获得的轨迹进行排序。
我们的结果表明,与已知的多激酶抑制剂达沙替尼相比,三种命中化合物对 ACK1 显示出更高的结合亲和力。Hit1 和 Hit3 的分子间相互作用表明,化合物与守门员 T205、铰链区 A208 和 DFG 基序 D270 形成理想的氢键相互作用。因此,我们预计所提出的支架可能有助于设计有前途的选择性 ACK1 抑制剂。