Recent Advances in Predicting G-Protein Coupled Receptor Classification
This situation has challenged us to develop automated methods by which one can predict the family and sub-family classes of GPCRs based on the information of their primary sequences alone, so as to facilitate classifying drugs, a technique called “evolutionary pharmacology” often used in pharmaceutical industries for drug development. In the past eight years, various computational methods were proposed. This review is devoted to summarize their development. Meanwhile, the future challenge in this area has also been briefly addressed.
Keywords: Cellular automata; G-protein coupled receptor; enzyme-substrate; evolutionary pharmacology; homology bias; protein sequence image expression; pseudo amino acid composition; redundancy; sequence-derived features; transmembrane
Document Type: Research Article
Affiliations: Computer Department, Jing- De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China.
Publication date: June 1, 2012
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