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Molecular & Cellular Proteomics 3:93-104, 2004.
© 2004 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Identification of the Substrates and Interaction Proteins of Aurora Kinases from a Protein-Protein Interaction Model ^{* ,S}

An-Chi Tien, Ming-Hong Lin, Li-Jen Su^,, Yi-Ren Hong^¶, Tai-Shan Cheng^¶, Yuan-Chii G. Lee^,||, Wey-Jinq Lin^**, Ivan H. Still and Chi-Ying F. Huang^,,,¶¶,||||

From the Division of Molecular and Genomic Medicine, National Health Research Institutes, Taipei 115, Taiwan, Republic of China; Graduate Institute of Life Sciences, National Defense Medical Center, Taipei 114, Taiwan, Republic of China; ^¶ Graduate Institute of Biochemistry, Kaohsiung Medical University, Kaohsiung 807, Taiwan, Republic of China; ^|| Graduate Institute of Medical Informatics, Taipei Medical University, Taipei 110, Taiwan, Republic of China; ^** Biopharmaceutical Science, National Yang-Ming University, Taipei 112, Taiwan, Republic of China; Department of Cancer Genetics, Roswell Park Cancer Institute, Buffalo, NY 14263; Institute of Biotechnology in Medicine; National Yang-Ming University, Taipei 112, Taiwan, Republic of China; and ^¶¶ Department of Computer Science and Information Engineering, National Taiwan University, Taipei 106, Taiwan, Republic of China

The increasing use of high-throughput and large-scale bioinformatics-based studies has generated a massive amount of data stored in a number of different databases. The major need now is to explore this disparate data to find biologically relevant interactions and pathways. Thus, in the post-genomic era, there is clearly a need for the development of algorithms that can accurately predict novel protein-protein interaction networks in silico. The evolutionarily conserved Aurora family kinases have been chosen as a model for the development of a method to identify novel biological networks by a comparison of human and various model organisms. Our search methodology was designed to predict and prioritize molecular targets for Aurora family kinases, so that only the most promising are subjected to empirical testing. Four potential Aurora substrates and/or interacting proteins, TACC3, survivin, Hec1, and hsNuf2, were identified and empirically validated. Together, these results justify the timely implementation of in silico biology in routine wet-lab studies and have also allowed the application of a new approach to the elucidation of protein function in the post-genomic era.

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