The selective coupling of G-protein-coupled receptors (GPCRs) to specific G proteins is critical to trigger the appropriate physiological response. However, the determinants of selective binding have remained elusive. Here we reveal the existence of a selectivity barcode (that is, patterns of amino acids) on each of the 16 human G proteins that is recognized by distinct regions on the approximately 800 human receptors. Although universally conserved positions in the barcode allow the receptors to bind and activate G proteins in a similar manner, different receptors recognize the unique positions of the G-protein barcode through distinct residues, like multiple keys (receptors) opening the same lock (G protein) using non-identical cuts. Considering the evolutionary history of GPCRs allows the identification of these selectivity-determining residues. These findings lay the foundation for understanding the molecular basis of coupling selectivity within individual receptors and G proteins.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Nature Communications Open Access 20 September 2022
Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression
Nature Communications Open Access 18 July 2022
Nature Communications Open Access 15 March 2022
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Bjarnadóttir, T. K. et al. Comprehensive repertoire and phylogenetic analysis of the G protein-coupled receptors in human and mouse. Genomics 88, 263–273 (2006)
Anantharaman, V., Abhiman, S., de Souza, R. F. & Aravind, L. Comparative genomics uncovers novel structural and functional features of the heterotrimeric GTPase signaling system. Gene 475, 63–78 (2011)
Southan, C. et al. The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. Nucleic Acids Res. 44 (D1), D1054–D1068 (2016)
Isberg, V. et al. Generic GPCR residue numbers—aligning topology maps while minding the gaps. Trends Pharmacol. Sci. 36, 22–31 (2015)
Neves, S. R., Ram, P. T. & Iyengar, R. G protein pathways. Science 296, 1636–1639 (2002)
Marinissen, M. J. & Gutkind, J. S. G-protein-coupled receptors and signaling networks: emerging paradigms. Trends Pharmacol. Sci. 22, 368–376 (2001)
Oldham, W. M. & Hamm, H. E. Heterotrimeric G protein activation by G-protein-coupled receptors. Nature Rev. Mol. Cell Biol. 9, 60–71 (2008)
Frielle, T. et al. Cloning of the cDNA for the human β1-adrenergic receptor. Proc. Natl Acad. Sci. USA 84, 7920–7924 (1987)
Ruat, M. et al. A novel rat serotonin (5-HT6) receptor: molecular cloning, localization and stimulation of cAMP accumulation. Biochem. Biophys. Res. Commun. 193, 268–276 (1993)
Li, F., De Godoy, M. & Rattan, S. Role of adenylate and guanylate cyclases in β1-, β2-, and β3-adrenoceptor-mediated relaxation of internal anal sphincter smooth muscle. J. Pharmacol. Exp. Ther. 308, 1111–1120 (2004)
Wess, J. Molecular basis of receptor/G-protein-coupling selectivity. Pharmacol. Ther. 80, 231–264 (1998)
Horn, F., van der Wenden, E. M., Oliveira, L., IJzerman, A. P. & Vriend, G. Receptors coupling to G proteins: is there a signal behind the sequence? Proteins 41, 448–459 (2000)
Wong, S. K. G protein selectivity is regulated by multiple intracellular regions of GPCRs. Neurosignals 12, 1–12 (2003)
Kruse, A. C. et al. Structure and dynamics of the M3 muscarinic acetylcholine receptor. Nature 482, 552–556 (2012)
Rasmussen, S. G. et al. Crystal structure of the β2 adrenergic receptor–Gs protein complex. Nature 477, 549–555 (2011)
Carpenter, B., Nehmé, R., Warne, T., Leslie, A. G. & Tate, C. G. Structure of the adenosine A2A receptor bound to an engineered G protein. Nature 536, 104–107 (2016)
Masuho I. et al. Distinct profiles of functional discrimination among G proteins determine the actions of G protein-coupled receptors. Sci. Signal. 8, ra123 (2015)
Krishnan, A. et al. Evolutionary hierarchy of vertebrate-like heterotrimeric G protein families. Mol. Phylogenet. Evol. 91, 27–40 (2015)
de Mendoza, A., Sebé-Pedrós, A. & Ruiz-Trillo, I. The evolution of the GPCR signaling system in eukaryotes: modularity, conservation, and the transition to metazoan multicellularity. Genome Biol. Evol. 6, 606–619 (2014)
Krishnan, A., Almén, M. S., Fredriksson, R. & Schiöth, H. B. The origin of GPCRs: identification of mammalian like Rhodopsin, Adhesion, Glutamate and Frizzled GPCRs in fungi. PLoS ONE 7, e29817 (2012)
Mirny, L. A. & Gelfand, M. S. Using orthologous and paralogous proteins to identify specificity determining residues. Genome Biol. 3, http://dx.doi.org/10.1186/gb-2002-3-3-preprint0002 (2002)
Flock, T. et al. Universal allosteric mechanism for Gα activation by GPCRs. Nature 524, 173–179 (2015)
Sun, D. et al. Probing Gαi1 protein activation at single-amino acid resolution. Nature Struct. Mol. Biol. 22, 686–694 (2015)
Conklin, B. R., Farfel, Z., Lustig, K. D., Julius, D. & Bourne, H. R. Substitution of three amino acids switches receptor specificity of Gqα to that of Giα. Nature 363, 274–276 (1993)
Komatsuzaki, K. et al. A novel system that reports the G-proteins linked to a given receptor: a study of type 3 somatostatin receptor. FEBS Lett. 406, 165–170 (1997)
Sasamura, H. et al. Analysis of Gα protein recognition profiles of angiotensin II receptors using chimeric Gα proteins. Mol. Cell. Endocrinol. 170, 113–121 (2000)
Janin, J. & Chothia, C. The structure of protein-protein recognition sites. J. Biol. Chem. 265, 16027–16030 (1990)
Venkatakrishnan, A. J. et al. Molecular signatures of G-protein-coupled receptors. Nature 494, 185–194 (2013)
Reichmann, D. et al. The modular architecture of protein-protein binding interfaces. Proc. Natl Acad. Sci. USA 102, 57–62 (2005)
Kleinau, G. et al. Principles and determinants of G-protein coupling by the rhodopsin-like thyrotropin receptor. PLoS ONE 5, e9745 (2010)
Isberg, V. et al. GPCRdb: an information system for G protein-coupled receptors. Nucleic Acids Res. 44 (D1), D356–D364 (2016)
Furness, S. G. et al. Ligand-dependent modulation of G protein conformation alters drug efficacy. Cell 167, 739–749 (2016)
Rose, A. S. et al. Position of transmembrane helix 6 determines receptor G protein coupling specificity. J. Am. Chem. Soc. 136, 11244–11247 (2014)
Wichard, J. D. et al. Chemogenomic analysis of G-protein coupled receptors and their ligands deciphers locks and keys governing diverse aspects of signalling. PLoS ONE 6, e16811 (2011)
Pawson, A. J. et al. The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands. Nucleic Acids Res. 42, D1098–D1106 (2014)
Finn, R. D. et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44 (D1), D279–D285 (2016)
UniProt Consortium. UniProt: a hub for protein information. Nucleic Acids Res. 43, D204–D212 (2015)
Wuster, A., Venkatakrishnan, A. J., Schertler, G. F. & Babu, M. M. Spial: analysis of subtype-specific features in multiple sequence alignments of proteins. Bioinformatics 26, 2906–2907 (2010)
Fredriksson, R. & Schiöth, H. B. The repertoire of G-protein-coupled receptors in fully sequenced genomes. Mol. Pharmacol. 67, 1414–1425 (2005)
Altenhoff, A. M., Schneider, A., Gonnet, G. H. & Dessimoz, C. OMA 2011: orthology inference among 1000 complete genomes. Nucleic Acids Res. 39, D289–D294 (2011)
Vilella, A. J. et al. EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates. Genome Res. 19, 327–335 (2009)
Finn, R. D. et al. HMMER web server: 2015 update. Nucleic Acids Res. 43 (W1), W30–W38 (2015)
Putnam, N. H. et al. Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organization. Science 317, 86–94 (2007)
Srivastava, M. et al. The Trichoplax genome and the nature of placozoans. Nature 454, 955–960 (2008)
Paradis, E ., Claude, J . & Strimmer, K. APE: Analyses of Phylogenetics and Evolution in R language. Bioinformatics 20, 289–290 (2004)
Ruan, J. et al. TreeFam: 2008 Update. Nucleic Acids Res. 36, D735–D740 (2008)
Pei, J., Sadreyev, R. & Grishin, N. V. PCMA: fast and accurate multiple sequence alignment based on profile consistency. Bioinformatics 19, 427–428 (2003)
Krissinel, E. & Henrick, K. Inference of macromolecular assemblies from crystalline state. J. Mol. Biol. 372, 774–797 (2007)
Rost, B. & Sander, C. Conservation and prediction of solvent accessibility in protein families. Proteins 20, 216–226 (1994)
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003)
Shannon, P. T., Grimes, M., Kutlu, B., Bot, J. J. & Galas, D. J. RCytoscape: tools for exploratory network analysis. BMC Bioinformatics 14, 217 (2013)
Su, G ., Kuchinsky, A ., Morris, J. H ., States, D. J . & Meng, F. GLay: community structure analysis of biological networks. Bioinformatics 26, 3135–3137 (2010)
Morris, J. H. et al. clusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC Bioinformatics 12, 436 (2011)
Doncheva, N. T., Assenov, Y., Domingues, F. S. & Albrecht, M. Topological analysis and interactive visualization of biological networks and protein structures. Nature Protocols 7, 670–685 (2012)
Liu, Y., Schmidt, B. & Maskell, D. L. MSAProbs: multiple sequence alignment based on pair hidden Markov models and partition function posterior probabilities. Bioinformatics 26, 1958–1964 (2010)
Konagurthu, A. S ., Whisstock, J. C ., Stuckey, P. J . & Lesk, A. M. MUSTANG: a multiple structural alignment algorithm. Proteins 64, 559–574 (2006)
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010)
Kumar, S., Stecher, G. & Tamura, K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33, 1870–1874 (2016)
Crooks, G. E., Hon, G., Chandonia, J. M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004)
Letunic, I. & Bork, P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44 (W1), W242–W245 (2016)
Grant, B. J., Rodrigues, A. P., ElSawy, K. M., McCammon, J. A. & Caves, L. S. Bio3d: an R package for the comparative analysis of protein structures. Bioinformatics 22, 2695–2696 (2006)
We thank U. F. Lang, D. Veprintsev, C. Ravarani, H. Harbrecht, G. De Baets, D. Prado, X. Deupi, C. G. Tate and N. S. Latysheva for their comments on this work, and J. Westmoreland for assistance with Fig. 6. We thank S. Chavali and B. Lang for help with compiling mutation and expression data. We thank M. Mounir and C. Munk for help with the GPCRdb web service. This work was supported by the Medical Research Council (MC_U105185859; M.M.B., T.F., S.B.), the Boehringer Ingelheim Fond (T.F.), European Research Council (DE-ORPHAN 639125; D.E.G., A.S.H., N.L.) and the Lundbeck Foundation (R163-2013-16327; D.E.G.). T.F. is a Research Fellow of Fitzwilliam College, University of Cambridge, UK. M.M.B. is a Lister Institute Research Prize Fellow and is supported by a European Research Council Consolidator Grant.
The authors declare no competing financial interests.
Reviewer Information Nature thanks M. Lassig, A. B. Tobin and the other anonymous reviewer(s) for their contribution to the peer review of this work.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Number of GPCRs with distinct primary signal transduction (G-protein coupling) for each GPCR family as annotated in the IUPHAR/BPS Guide to Pharmacology database (GtoPdb). Only ‘primary transduction’, as defined by the database, is shown here. Note that Fig. 1c, d shows both primary and secondary coupling. b, Number of GPCRs with distinct primary signal transduction properties grouped by GPCR class.
The gene expression level (transcriptome) of human G proteins (top) and GPCRs (bottom) across 84 healthy tissues or cell types is shown. The right insets show histograms of the number of G proteins (blue) or GPCRs (red) that are expressed in one or multiple tissues. This highlights that at least one member of each G-protein subfamily (Gαs, Gαi/o, Gαq/11, Gα12/13) is ubiquitously expressed in most tissues. Other subtypes, such as Gαt, are more tissue-specific. GPCRs, on the other hand, seem to be much more tissue-specific and are only expressed in single or few tissues, except for some ubiquitously expressed GPCRs such as chemokine receptors. Normalized expression data were derived from BioGPS (http://biogps.org).
a, The GPCR and Gα protein repertoires (unique genes) across 13 representative organisms determined using Pfam domain annotations (see Methods and Supplementary Table). The number of class A receptors slightly differs from the IUPHAR/BPS Guide to Pharmacology database as class A taste receptors are classified as a separate Pfam family. b, The lineage-specific expansion and differentiation of the GPCR and G-protein repertoires during evolution. The numbers of G proteins and GPCRs are shown for C. owczarzaki (an early-branching unicellular sister group of metazoans), T. adhaerens (one of the oldest known multicellular organism) and humans.
a, Estimation of the ‘phylogenetic age’ of human GPCRs and G proteins by identifying the most distant one-to-one orthologues (dark grey) or any orthologue (light grey) from 215 organisms in the OMA database. The ‘phylogenetic age’ was determined by the branching times of humans and the oldest organisms that share either a one-to-one orthologue or any orthologue (one–many or many–one or many–many) with the human gene (Methods). The classification of GPCRs follows the IUPHAR receptor classification. b, Complete table of the GPCR and G-protein repertoire and the phylogenetic ‘overlap’ of the protein repertoires. The Jaccard similarity index (Methods) was used for the GPCR and G-protein repertoires in the 12 completely sequenced genomes from the different eukaryotic lineages. The subscripts ‘u’ and ‘s’ for organisms A and B refer to the number of unique and shared genes, respectively.
Extended Data Figure 5 Conservation of residue positions among orthologues and paralogues in Gα proteins.
a, Jitterplots showing the degree of sequence conservation (sequence identity) of each CGN position in Gα proteins. The plots show the degree of conservation in each one-to-one orthologue alignment for each Gα subtype versus the conservation of the human paralogue alignment (alignments are provided as Supplementary Data and can be visualized to identify which amino acids were fixed at what time points during evolution). b, Boxplot showing the distribution of the relative accessible surface area of residue positions in each group for Gαs (mapped onto Gαi with PDB accession number 1GP2). c, The conserved positions at the interface of the β2AR–Gαs (PDB accession number 3SN6) form central clusters (magenta) and tend to be surrounded by selectivity-determining positions (blue). The average distances among positions are conserved-to-conserved: 9.84 Å, conserved-to-specific: 11.23 Å, specific-to-specific: 12.20 Å.
Extended Data Figure 6 Integration of sequence- and structure-derived information to understand how GPCRs read the G-protein selectivity barcode.
a, G-protein selectivity barcode (Fig. 3d) mapped onto the GPCR–G-protein interface clusters obtained using the β2AR–Gαs complex structure (Fig. 4 and Methods) highlights which regions of the GPCR contact selectivity-determining residues on the G protein. Nodes represent GPCR (rounded squares) and G-protein (circles) positions. The edges and their width represent the number of atomic contacts between residues. The size of the nodes is relative to their node degree (number of contacts to other nodes, which is a measure of how central a node is). Residues within the cluster are grouped and coloured differently in the background (red, blue, green, brown and yellow). b, Statistics highlighting the results from integrating the G-protein barcode analysis (sequence-based analysis) with the structural clustering analysis (structure-based analysis). The number of residues in Gαs with a particular sequence conservation property in each cluster (that is, universally conserved, neutrally evolving, selectivity-determining position) is shown. The numbers of residues that map to the different GPCR and G-protein secondary structure elements are shown both for GPCR and for G protein on the basis of the β2AR–Gαs complex structure (PDB accession number 3SN6).
Extended Data Figure 7 Comparison of the interface contacts and the contacting residues between β2AR–Gαs and A2AR–mini Gαs.
a, Comparison of the overall structure of both complex structures shows that the two receptors bind the G protein in a similar binding mode. Root mean square deviation values are provided in the figure. b, Detailed comparison of the residue contacts between equivalent positions of β2AR and A2AR receptor with equivalent positions of Gαs and the mini Gαs construct used to obtain the complex structures. The exact residue and the GPCRdb numbering scheme for the receptor and the CGN system for the G protein are shown on the axes. Contacts (coloured cells in the matrix) and positions (horizontal and vertical coloured bars next to the axes) that are common or unique to the β2AR–Gαs or A2AR–mini Gαs complex are shown in different colours. The G-protein selectivity barcode as in Fig. 3 is shown in the bottom of the matrix. This analysis suggests that while the same positions of the G protein and GPCRs may be involved in the recognition, distinct residues (both positions and the amino-acid residue) on the two different receptors contact them. In other words, the same selectivity barcode presented by Gαs is read differently by receptors belonging to different subtypes.
Extended Data Figure 8 Phylogenetic tree of GPCRs and mapping of ancestral reconstruction of coupling selectivity.
A phylogenetic tree of human class A, B and C GPCRs was derived from a full-length GPCR multiple sequence alignment that was created in-house (Methods). Concentric circles illustrate the G-protein coupling selectivity of each GPCR: the four dots depict both primary and secondary G-protein coupling (from inside to outside: Gαs, Gαi/o, Gαq/11, Gα12/13). The inset on the top left shows a magnification of one clade in the phylogenetic tree. G-protein coupling of each ancestral node was reconstructed by considering only the primary coupling of the receptors (Methods).
a, Using the phylogenetic history to define receptor clades with a common ancestor uncovers distinct conserved properties of amino acids at specific interface positions on the receptor. The figure shows molecular property signatures (ability of residues at a given G-protein interface position to mediate a distinct type of molecular interaction) on the intracellular interface of GPCRs. Each circle represents a property (coloured) and its distinctiveness (sizing) within the receptors that couple to the given G-protein subtype (versus those that do not). There is no conserved sequence pattern in all the receptors that couple to the same Gα protein. b, Receptors that form a phylogenetic clade exhibit distinct molecular property signatures (Methods). The legend (bottom) shows the colour scheme used for amino acids with different properties. c, Sequence pattern determined by Spial (Methods) of the interface positions (left). Top: clades of vasopressin 2 receptor (V2R) and β-adrenoreceptors (βARs), which belong to different groups, both couple to Gαs. However, the common ancestor of the V2R-related receptor coupled to Gαq (suggesting alteration of selectivity) whereas the common ancestor of aminergic receptors coupled to Gαs proteins (suggesting inheritance of selectivity). An analysis of the equivalent interface positions on the receptor that contact the Gα protein shows that V2R independently accumulated a different set of mutations in the same region to selectively couple to Gαs and hence arrived at a different sequence pattern to read the selectivity barcode on Gαs. Bottom: adenosine-clade and βARs (which belong to different groups) that both couple to Gαs and have complex evolutionary histories (Extended Data Fig. 8). An analysis of the equivalent interface positions on the receptor that contact the Gα protein shows that A2AR independently accumulated a different set of mutations in the same region to couple to Gαs and hence arrived at a different sequence pattern to read the same selectivity barcode on Gαs (see also Extended Data Fig. 7b). Mutagenesis of the A2B receptor has shown that the positions 3x50, 3x54, 5x69, 6x36 and 6x37 affect the coupling of Gα proteins Gαq, Gα12, Gα13, Gα14, Gαi1, Gαi2 and Gα15 (see also Supplementary Table 1).
Summary of the features in GPCRdb, describing the receptor–G-protein binding interface. These features allow users to investigate various aspects of receptor–G-protein binding selectivity and G-protein-specific information for all the human GPCRs and G proteins.
This zipped file contains Supplementary Table 1, Supplementary Data files 1-2, Supplementary Figure 1 and 2 additional Supplementary Data files – see the Supplementary Guide file within the zipped folder for more details. (ZIP 1207 kb)
About this article
Cite this article
Flock, T., Hauser, A., Lund, N. et al. Selectivity determinants of GPCR–G-protein binding. Nature 545, 317–322 (2017). https://doi.org/10.1038/nature22070
Cell Communication and Signaling (2022)
Nature Communications (2022)
Nature Communications (2022)
Intrinsically disordered proteins and proteins with intrinsically disordered regions in neurodegenerative diseases
Biophysical Reviews (2022)
Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression
Nature Communications (2022)