Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches

Abstract

Background: 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. Methods: 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. Results: 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.

Keywords

• ACK1
• pharmacophore modeling
• docking
• molecular dynamics simulations
• cancer
• inhibitor