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Published October 1, 2002 | Published
Journal Article Open

Prediction of structure and function of G protein-coupled receptors

Abstract

G protein-coupled receptors (GPCRs) mediate our sense of vision, smell, taste, and pain. They are also involved in cell recognition and communication processes, and hence have emerged as a prominent superfamily for drug targets. Unfortunately, the atomic-level structure is available for only one GPCR (bovine rhodopsin), making it difficult to use structure-based methods to design drugs and mutation experiments. We have recently developed first principles methods (MembStruk and HierDock) for predicting structure of GPCRs, and for predicting the ligand binding sites and relative binding affinities. Comparing to the one case with structural data, bovine rhodopsin, we find good accuracy in both the structure of the protein and of the bound ligand. We report here the application of MembStruk and HierDock to β1-adrenergic receptor, endothelial differential gene 6, mouse and rat I7 olfactory receptors, and human sweet receptor. We find that the predicted structure of β1-adrenergic receptor leads to a binding site for epinephrine that agrees well with the mutation experiments. Similarly the predicted binding sites and affinities for endothelial differential gene 6, mouse and rat I7 olfactory receptors, and human sweet receptor are consistent with the available experimental data. These predicted structures and binding sites allow the design of mutation experiments to validate and improve the structure and function prediction methods. As these structures are validated they can be used as targets for the design of new receptor-selective antagonists or agonists for GPCRs.

Additional Information

© 2002 National Academy of Sciences. Contributed by William A. Goddard III, June 14, 2002. This research was initiated with support from Army Research Office–Multidisciplinary University Research Initiative (MURI) (Grant DAAG55-98-1-0266) and continued with National Institutes of Health support (Grants R01-GM62253-01, R01-AI40567, and R01-CA85779). We particularly want to thank IBM for a Shared University Research grant that provided the computational facilities that made this work possible. The facilities of Materials and Process Simulation Center are also supported by grants from the Department of Energy–Accelerated Strategic Compliance Initiative, Army Research Office-Defense University Research Instrumentation Program, Army Research Office-MURI, the National Institutes of Health, the National Science Foundation, Chevron–Texaco, General Motors, 3M, Avery–Dennison, Seiko–Epson, Kellogg's, Beckman Institute, and Asahi Kasei.

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