A Computational Workflow for the Identification of Novel Fragments Acting as Inhibitors of the Activity of Protein Kinase CK1δ

Int J Mol Sci. 2021 Sep 9;22(18):9741. doi: 10.3390/ijms22189741.

Abstract

Fragment-Based Drug Discovery (FBDD) has become, in recent years, a consolidated approach in the drug discovery process, leading to several drug candidates under investigation in clinical trials and some approved drugs. Among these successful applications of the FBDD approach, kinases represent a class of targets where this strategy has demonstrated its real potential with the approved kinase inhibitor Vemurafenib. In the Kinase family, protein kinase CK1 isoform δ (CK1δ) has become a promising target in the treatment of different neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. In the present work, we set up and applied a computational workflow for the identification of putative fragment binders in large virtual databases. To validate the method, the selected compounds were tested in vitro to assess the CK1δ inhibition.

Keywords: fragment-based drug discovery; molecular docking; molecular dynamics; protein kinase CK1δ; supervised molecular dynamics.

MeSH terms

  • Binding Sites
  • Casein Kinase Idelta / antagonists & inhibitors*
  • Casein Kinase Idelta / chemistry*
  • Drug Discovery / methods*
  • Humans
  • Models, Molecular*
  • Molecular Conformation
  • Molecular Docking Simulation
  • Molecular Dynamics Simulation
  • Protein Binding
  • Protein Kinase Inhibitors / chemistry*
  • Protein Kinase Inhibitors / pharmacology*
  • Structure-Activity Relationship
  • Workflow

Substances

  • Protein Kinase Inhibitors
  • Casein Kinase Idelta