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Mol. Cells 2009; 28(3): 195-200

Published online September 4, 2009

https://doi.org/10.1007/s10059-009-0122-z

© The Korean Society for Molecular and Cellular Biology

A Computational Approach for the Classifi-cation of Protein Tyrosine Kinases

Hyun-Chul Park, Hae-Seok Eo, and Won Kim

Received: July 8, 2009; Accepted: July 20, 2009

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 struc-tural 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 classification, motifs and transmembrane domain, profile hidden Markov model, protein tyrosine kinase, receptor tyrosine kinase

Article

Research Article

Mol. Cells 2009; 28(3): 195-200

Published online September 30, 2009 https://doi.org/10.1007/s10059-009-0122-z

Copyright © The Korean Society for Molecular and Cellular Biology.

A Computational Approach for the Classifi-cation of Protein Tyrosine Kinases

Hyun-Chul Park, Hae-Seok Eo, and Won Kim

Received: July 8, 2009; Accepted: July 20, 2009

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 struc-tural 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: classification, motifs and transmembrane domain, profile hidden Markov model, protein tyrosine kinase, receptor tyrosine kinase

Mol. Cells
Jun 30, 2023 Vol.46 No.6, pp. 329~398
COVER PICTURE
The cellular proteostasis network is adaptively modulated upon cellular stress, thereby protecting cells from proteostasis collapse. Heat shock induces the translocation of misfolded proteins and the chaperone protein HSP70 into nucleolus, where nuclear protein quality control primarily occurs. Nuclear RNA export factor 1 (green), nucleolar protein fibrillarin (red), and nuclei (blue) were visualized in NIH3T3 cells under basal (left) and heat shock (right) conditions (Park et al., pp. 374-386).

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