期刊
AMINO ACIDS
卷 30, 期 4, 页码 397-402出版社
SPRINGER WIEN
DOI: 10.1007/s00726-006-0332-z
关键词
G-protein coupled receptors; nuclear receptors; hydrophobicity; fast Fourier transform; power spectrum; support vector machine
As the potential drug targets, G-protein coupled receptors (GPCRs) and nuclear receptors (NRs) are the focuses in pharmaceutical research. It is of great practical significance to develop an automated and reliable method to facilitate the identification of novel receptors. In this study, a method of fast Fourier transform-based support vector machine was proposed to classify GPCRs and NRs from the hydrophobicity of proteins. The models for all the GPCR families and NR subfamilies were trained and validated using jackknife test and the results thus obtained are quite promising. Meanwhile, the performance of the method was evaluated on GPCR and NR independent datasets with good performance. The good results indicate the applicability of the method. Two web servers implementing the prediction are available at htttp://chem.scu.edu.cn/blast/Pred-GPCR and http://chem.edu.cn/blast/Pred-NR.
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