Deciphering the evolution of G protein-coupled receptors in vertebrates

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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G protein-coupled receptors (GPCRs) are ancestrally related membrane proteins on cells that mediate the pharmacological effect of most drugs and neurotransmitters. GPCRs are the largest group of membrane receptor proteins encoded in the human genome. Using the case study of vertebrate opioid receptors, this chapter introduces an evolutionary approach to understanding pharmacological selectivity, predicted from sequence analysis, and confirmed by experimental studies. The same approach can be used to examine receptor function and applies to other families of GPCRs besides the opioid receptor family. Opioid receptors consist of a family of four closely related proteins expressed in all vertebrates examined. The three types of opioid receptors shown unequivocally to mediate analgesia in animal models and in humans are the mu (MOR), delta (DOR), and kappa (KOR) opioid receptor proteins. The role of the fourth member of the opioid receptor family, the nociceptin or orphanin FQ receptor (ORL), in producing analgesia is not as clear. There are now cDNA sequences for all four types of opioid receptors that are expressed in the brain of six species from three different classes of vertebrates. This chapter presents a comparative analysis of vertebrate opioid receptors using bioinformatics and data from recent human genome studies. Results indicate that opioid receptor genes most likely arose by gene duplication, that there appears to be an evolutionary vector of opioid receptor type divergence in sequence and function, and that the hMOR gene shows evidence of positive selection or adaptive evolution in Homo sapiens. Additionally, unlike many typical reviews, this paper highlights the methods used to come to these conclusions.

Original languageEnglish
Title of host publicationMethods for the Discovery and Characterization of G Protein-Coupled Receptors
EditorsCraig W. Stevens
Number of pages32
StatePublished - 2011

Publication series

ISSN (Print)0893-2336
ISSN (Electronic)1940-6045


  • Bioinformatics
  • Gene duplication
  • Molecular evolution
  • Opioid receptors
  • Positive selection


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