| Title: | Prediction of G-protein-coupled receptor classes |
| Address: | "Gordon Life Science Institute, 13784 Torrey Del Mar, San Diego, CA 92130, USA. kchou@san.rr.com" |
| ISSN/ISBN: | 1535-3893 (Print) 1535-3893 (Linking) |
| Abstract: | "Being the largest family of cell surface receptors, G-protein-coupled receptors (GPCRs) are among the most frequent targets of therapeutic drugs. The functions of many of GPCRs are unknown, and it is both time-consuming and expensive to determine their ligands and signaling pathways. This forces us to face a critical challenge: how to develop an automated method for classifying the family of GPCRs so as to help us in classifying drugs and expedite the process of drug discovery. Owing to their highly divergent nature, it is difficult to predict the classification of GPCRs by means of conventional sequence alignment approaches. To cope with such a situation, the CD (Covariant Discriminant) predictor was introduced to predict the families of GPCRs. The overall success rate thus obtained by jack-knife test for 1238 GPCRs classified into three main families, i.e., class A-'rhodopsin like', class B-'secretin like', and class C-'metabotrophic/glutamate/pheromone', was over 97%. The high success rate suggests that the CD predictor holds very high potential to become a useful tool for understanding the actions of drugs that target GPCRs and designing new medications with fewer side effects and greater efficacy" |
| Keywords: | "Amino Acids/analysis Databases, Protein Drug Design Humans Mathematics Models, Molecular Molecular Sequence Data Receptors, G-Protein-Coupled/*chemistry/*classification/genetics Second Messenger Systems;" |
| Notes: | "MedlineChou, Kuo-Chen eng 2005/08/09 J Proteome Res. 2005 Jul-Aug; 4(4):1413-8. doi: 10.1021/pr050087t" |
