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Published March 16, 2004 | Published
Journal Article Open

The predicted 3D structure of the human D2 dopamine receptor and the binding site and binding affinities for agonists and antagonists

Abstract

Dopamine neurotransmitter and its receptors play a critical role in the cell signaling process responsible for information transfer in neurons functioning in the nervous system. Development of improved therapeutics for such disorders as Parkinson's disease and schizophrenia would be significantly enhanced with the availability of the 3D structure for the dopamine receptors and of the binding site for dopamine and other agonists and antagonists. We report here the 3D structure of the long isoform of the human D2 dopamine receptor, predicted from primary sequence using first-principles theoretical and computational techniques (i.e., we did not use bioinformatic or experimental 3D structural information in predicting structures). The predicted 3D structure is validated by comparison of the predicted binding site and the relative binding affinities of dopamine, three known dopamine agonists (antiparkinsonian), and seven known antagonists (antipsychotic) in the D2 receptor to experimentally determined values. These structures correctly predict the critical residues for binding dopamine and several antagonists, identified by mutation studies, and give relative binding affinities that correlate well with experiments. The predicted binding site for dopamine and agonists is located between transmembrane (TM) helices 3, 4, 5, and 6, whereas the best antagonists bind to a site involving TM helices 2, 3, 4, 6, and 7 with minimal contacts to TM helix 5. We identify characteristic differences between the binding sites of agonists and antagonists.

Additional Information

© 2004 by the National Academy of Sciences. Contributed by William A. Goddard III, January 6, 2004. Published online before print March 3, 2004, 10.1073/pnas.0400100101 This research was initiated with support from the Army Research Office (ARO) Multidiciplinary University Research Initiative (MURI) and was completed with support from National Institutes of Health Grants BRGRO1-GM625523, R29AI40567, and HD36385. The computational facilities were provided by a Shared University Research grant from IBM and Defense University Research Instrumentation Program grants from ARO and the Office of Naval Research (ONR). The facilities of the Materials and Process Simulation Center are also supported by the Department of Energy in addition to the National Science Foundation, ARO-MURI, MURI-ONR, General Motors, ChevronTexaco, Seiko–Epson, the Beckman Institute, and Asahi Kasei.

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