title: Computational design and experimental characterization of GPCR segment models.
abstract: G-protein-coupled receptors (GPCRs) are membrane proteins with high significance as therapeutic targets. The GPCR family in humans includes over 800 different proteins, but high-resolution experimental structures of nearly complete structures are limited to only seven different family members. Additional structural data are expected to stimulate drug development efforts and an improved understanding of the basic signal transduction process. Characterization of GPCR three-dimensional structures is slowed by numerous intrinsic challenges, but similarities in the structures of the helical bundles of the currently available structures suggest that alternative methods focused on the more highly variable loop segments connecting the helical regions are of value. This chapter focuses on the design of GPCR segment models that spontaneously fold in solution to allow characterization of individual loop segments from any GPCR sequence, as well as how to establish appropriate conditions for structural studies and integrate the structures that result from such studies into computational models to produce hybrid homology-experimental GPCR structural models.
authors: Department of Chemistry, The University of Memphis, Memphis, Tennessee, USA. aparrill@memphis.edu
authors: Abby L
authors: AL
authors: Parrill
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D003198:Computer Simulation; D015870:Gene Expression; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017510:Protein Folding; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D018343:Receptors, Adrenergic, beta-2 / Q000737:chemistry* / Q000235:genetics / Q000302:isolation & purification; D011994:Recombinant Proteins / Q000737:chemistry / Q000235:genetics / Q000302:isolation & purification; D016415:Sequence Alignment; D040681:Structural Homology, Protein
chemical_list: D018343:Receptors, Adrenergic, beta-2; D011994:Recombinant Proteins