In silico structural and functional analysis of the human TOPK protein by structure modeling and molecular dynamics

Palani Kirubakaran1, Muthusamy Karthikeyan, Kh Dhanachandra Singh

  • 1Department of Bioinformatics, Science Block, Alagappa University, Karaikudi, 630 004, Tamil Nadu, India.

Insights

T-lymphokine-activated killer cell-originated protein kinase (TOPK) over expression is linked to cancer. This study modeled TOPK structure, identified potential inhibitors, and analyzed its interaction with CDK1, providing insights for drug design.

Area of Science:

  • Biochemistry
  • Structural Biology
  • Computational Chemistry

Background:

  • Overexpression of T-lymphokine-activated killer cell-originated protein kinase (TOPK) is implicated in various cancers, including leukemia and myeloma.
  • The precise function and regulatory mechanisms of TOPK in tumor cells remain largely unknown.
  • The absence of TOPK's crystal structure has hindered detailed mechanistic and structural studies.

Purpose of the Study:

  • To construct and refine a 3D model of the TOPK protein.
  • To identify potential TOPK inhibitors and analyze protein-ligand interactions.
  • To investigate the structural impact of TOPK mutations on its interaction with CDK1.

Main Methods:

  • 3D protein structure modeling using multiple templates.
  • Molecular dynamics (MD) simulations for model refinement and stability analysis.
  • APBS for electrostatic potential mapping, HTVS for lead molecule identification, and protein-protein docking.

Main Results:

  • A reliable 3D model of TOPK was generated, with an optimal stability pH of 3.4.
  • Potential lead molecules targeting TOPK's active site were identified, showing stable binding modes in simulations.
  • The wild-type TOPK-CDK1 complex demonstrated greater stability than the Thr9Ala mutant complex.

Conclusions:

  • The generated TOPK structural model provides a foundation for understanding its mechanism of action.
  • Identified lead molecules and structural insights can guide the development of novel TOPK inhibitors.
  • Structural data aids in understanding the impact of mutations on protein interactions, crucial for structure-based drug design.

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