Bioinformatical analysis of G-protein-coupled receptors

Abstract

G-protein-coupled receptors play a key role in cellular signaling networks that regulate various physiological processes, such as vision, smell, taste, neurotransmission, secretion, inflammatory, immune responses, cellular metabolism, and cellular growth. These proteins are very important for understanding human physiology and disease. Many efforts in pharmaceutical research have been aimed at understanding their structure and function. Unfortunately, because they are difficult to crystallize and most of them will not dissolve in normal solvents, so far very few G-protein-coupled receptor structures have been determined. In contrast, more than 1000 G-protein-coupled receptor sequences are known, and many more are expected to become known soon. In view of the extremely unbalanced state, it would be very useful to develop a fast sequence-based method to identify their different types. This would no doubt have practical value for both basic research and drug discovery because the function or binding specificity of a G-protein coupled receptor is determined by the particular type it belongs to. To realize this, a statistical analysis has been performed for 566 G-protein-coupled receptors classified into seven different types. The results indicate that the types of G-protein-coupled receptors are predictable to a considerable accurate extent if a good training data set can be established for such a goal.