Computer-aided design of selective inhibitors of LOK and SLK kinases

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  • February 27, 2019
Creator
  • Wang, Christopher
    • Affiliation: College of Arts and Sciences, Department of Chemistry
Abstract
  • SLK, a STE20-like serine/threonine protein kinase, and LOK/STK10, or lymphocyte oriented kinase/serine/threonine protein kinase 10, are thought to be involved in apoptosis and regulation of cell division. To further study the physiological roles of these two closely related and poorly-studied kinases, there is a need to discover selective chemical probes. Modeling chemogenomics data with Quantitative Structure Activity Relationship (QSAR) analysis is well-defined approach employed by computational chemists to predict the bioactivity of an untested compound. Here we show that QSAR models built on large curated chemogenomics datasets can help to prioritize and design inhibitors selective for SLK or LOK from the majority of related kinases within the STE20 subfamily. Twenty-six predictive QSAR models were developed on both Carolina Cheminformatics Workbench (ChemBench) and GUSAR software with CCR and Q2 values obtained by 5-fold external cross-validation of 0.6-0.85 and 0.67-0.94, respectively. Over three million compounds from the ZINC dataset were screened through these externally validated QSAR models. Two compounds were predicted to be selectively active for SLK and forty for LOK. Predicted activity of these compounds was in agreement with the results of molecular docking with Schrodinger GLIDE on crystal structures 4USF and 4USE. Selected compounds were recommended to the Structural Genomics Consortium in UNC for experimental testing.
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  • In Copyright
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  • Funding: None
Advisor
  • Muratov, Eugene
Degree
  • Bachelor of Science
Academic concentration
  • Chemistry
Honors level
  • Honors
Degree granting institution
  • University of North Carolina at Chapel Hill
Graduation year
  • 2017
Language
  • English

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