title: A study on the correlation of G-protein-coupled receptor types with amino acid composition.
abstract: G-protein-coupled receptors have become a target in utilizing bioinformatics and genomics technology to facilitate drug discovery for psychiatric diseases. In this study the covariant-discriminant algorithm [Chou and Elrod (1999) Protein Eng., 12, 107-118] has been used to analyze the correlation between the types of G-protein-coupled receptors and the amino acid composition. It has been found that different types of G-protein-coupled receptors are quite closely correlated with the amino acid composition, implying that the types of G-protein-coupled receptors are predictable to a considerably accurate extent if a good training data set can be established for that purpose. The method derived here can be also used to do preliminary classification of orphan G-protein-coupled receptors. This will significantly expedite the process of identifying proper G-protein-coupled receptors for drug discovery.
authors.affiliation: Computer-Aided Drug Discovery, Pharmacia, MI 49007-4940, USA.
authors.forename: David W
authors.initials: DW
authors.lastname: Elrod
authors.forename: Kuo-Chen
authors.initials: KC
authors.lastname: Chou
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000032:analysis; D030562:Databases, Protein; D015195:Drug Design; D019204:GTP-Binding Proteins / Q000378:metabolism*; D008958:Models, Molecular; D015202:Protein Engineering; D011956:Receptors, Cell Surface / Q000737:chemistry* / Q000378:metabolism
chemical_list: D000596:Amino Acids; D011956:Receptors, Cell Surface; D019204:GTP-Binding Proteins