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Dimerization in Aminergic G-Protein-Coupled Receptors:  Application of a Hidden-Site Class Model of Evolution

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Department of Chemistry, Biophysics Research Division, and Department of Pharmacology, University of Michigan, Ann Arbor, Michigan 48109, and Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London NW71AA, U.K.
Cite this: Biochemistry 2003, 42, 49, 14522–14531
Publication Date (Web):November 21, 2003
Copyright © 2003 American Chemical Society

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    G-Protein-coupled receptors (GPCRs) are an important superfamily of transmembrane proteins involved in cellular communication. Recently, it has been shown that dimerization is a widely occurring phenomenon in the GPCR superfamily, with likely important physiological roles. Here we use a novel hidden-site class model of evolution as a sequence analysis tool to predict possible dimerization interfaces in GPCRs. This model aims to simulate the evolution of proteins at the amino acid level, allowing the analysis of their sequences in an explicitly evolutionary context. Applying this model to aminergic GPCR sequences, we first validate the general reasoning behind the model. We then use the model to perform a family specific analysis of GPCRs. Accounting for the family structure of these proteins, this approach detects different evolutionarily conserved and accessible patches on transmembrane (TM) helices 4−6 in different families. On the basis of these findings, we propose an experimentally testable dimerization mechanism, involving interactions among different combinations of these helices in different families of aminergic GPCRs.

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     R.A.G. received support from NIH Grant LM0577. M.W.D. received support from NSF Grant 9726427. R.R.N. received support from NIH Grant HL46417. O.S.S. received support from the University of Michigan Bioinformatics Program.

     Department of Chemistry, University of Michigan.


     Biophysics Research Division, University of Michigan. Current address:  Department of Biological Statistics and Computational Biology, Cornell, Ithaca, NY 14853.

     Department of Pharmacology, University of Michigan.


     To whom correspondence should be addressed. E-mail:  [email protected]. Phone:  +44 (0)20 8816 2293. Fax:  +44 (0)20 8816 2460.

     National Institute for Medical Research.

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    16. Patricia H. Reggio. Computational Methods in Drug Design: Modeling G Protein-Coupled Receptor Monomers, Dimers, and Oligomers. 2008, 41-68.
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