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

Vikas Kumar1,2, Raj Kumar3, Shraddha Parate4,5

  • 1Department 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.

Biomolecules
|February 25, 2023
PubMed
Abstract

Insights

Researchers developed a pharmacophore model to identify novel inhibitors of Activated Cdc42-associated kinase (ACK1), a key target in cancer. Three hit compounds showed promising binding affinity, suggesting potential for new cancer therapies.

Area of Science:

  • Biochemistry
  • Molecular Biology
  • Drug Discovery

Background:

  • Activated Cdc42-associated kinase (ACK1) is crucial for cell growth, proliferation, and migration.
  • ACK1's role in receptor tyrosine kinase signaling makes it a target for antiproliferative cancer therapies.
  • Despite previous efforts, no ACK1-specific inhibitors have reached clinical application, highlighting the need for potent and selective agents.

Purpose of the Study:

  • To rationally design and identify novel, potent, and selective ACK1 inhibitors.
  • To utilize computational methods for screening and validating potential drug candidates against ACK1.

Main Methods:

  • A pharmacophore model was constructed using ACK1 crystal structures and known inhibitors.
  • A drug-like database was screened using the pharmacophore model.
  • Molecular docking and 500 ns all-atom molecular dynamics simulations were performed.
  • Binding free energy calculations and Gibb's free energy landscape analysis were used for ranking.

Main Results:

  • Three hit compounds demonstrated superior binding affinity to ACK1 compared to dasatinib.
  • Hit compounds formed favorable interactions, including hydrogen bonds with key residues like T205, A208, and D270.
  • The identified interactions support the potential of these compounds as ACK1 inhibitors.

Conclusions:

  • The study successfully identified potential ACK1 inhibitor scaffolds through computational screening.
  • The findings provide a foundation for the development of novel selective ACK1 inhibitors for cancer treatment.

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