Molecules and Cells

Korean Society for Molecular and Cellular Biology (한국분자세포생물학회)
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A Computational Approach for the Classification of Protein Tyrosine Kinases

  • Park, Hyun-Chul (Program in Bioinformatics, Seoul National University) ;
  • Eo, Hae-Seok (School of Computational Sciences, Korea Institute for Advanced Study) ;
  • Kim, Won (Program in Bioinformatics, Seoul National University)
  • Received : 2009.07.08
  • Accepted : 2009.07.20
  • Published : 2009.09.30
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Abstract

Protein tyrosine kinases (PTKs) play a central role in the modulation of a wide variety of cellular events such as differentiation, proliferation and metabolism, and their unregulated activation can lead to various diseases including cancer and diabetes. PTKs represent a diverse family of proteins including both receptor tyrosine kinases (RTKs) and non-receptor tyrosine kinases (NRTKs). Due to the diversity and important cellular roles of PTKs, accurate classification methods are required to better understand and differentiate different PTKs. In addition, PTKs have become important targets for drugs, providing a further need to develop novel methods to accurately classify this set of important biological molecules. Here, we introduce a novel statistical model for the classification of PTKs that is based on their structural features. The approach allows for both the recognition of PTKs and the classification of RTKs into their subfamilies. This novel approach had an overall accuracy of 98.5% for the identification of PTKs, and 99.3% for the classification of RTKs.

Keywords

Acknowledgement

Supported by : Ministry of Environment, Ministry of Land, Transport and Maritime Affairs of Korean government

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