Allosteric ligands control the activation of a class C GPCR heterodimer by acting at the transmembrane interface

  1. Lei Liu
  2. Zhiran Fan
  3. Xavier Rovira  Is a corresponding author
  4. Li Xue
  5. Salomé Roux
  6. Isabelle Brabet
  7. Mingxia Xin
  8. Jean-Philippe Pin  Is a corresponding author
  9. Philippe Rondard  Is a corresponding author
  10. Jianfeng Liu  Is a corresponding author
  1. Huazhong University of Science and Technology, China
  2. Spanish National Research Council, Spain
  3. University of Montpellier, CNRS, INSERM, France

Abstract

G protein-coupled receptors (GPCRs) are among the most promising drug targets. They often form homo- and heterodimers with allosteric cross-talk between receptor entities, which contributes to fine tuning of transmembrane signaling. Specifically controlling the activity of GPCR dimers with ligands is a good approach to clarify their physiological roles and to validate them as drug targets. Here, we examined the mode of action of positive allosteric modulators (PAMs) that bind at the interface of the transmembrane domains of the heterodimeric GABAB receptor. Our site-directed mutagenesis results show that mutations of this interface impact the function of the three PAM tested. The data support the inference that they act at the active interface between both transmembrane domains, the binding site involving residues of the TM6s of the GABAB1 and the GABAB2 subunit. Importantly, the agonist activity of these PAMs involves a key region in the central core of the GABAB2 transmembrane domain, which also controls the constitutive activity of the GABAB receptor. This region corresponds to the sodium ion binding site in class A GPCRs that controls the basal state of the receptors. Overall, these data reveal the possibility of developing allosteric compounds able to specifically modulate the activity of GPCR homo- and heterodimers by acting at their transmembrane interface.

Data availability

Figure 2- Source Data 1 contain the numerical data used to generate the figures;Figure 3 - Source Data 1 contain the numerical data used to generate the figures;Figure 4 - Source Data 1 contain the numerical data used to generate the figures;Figure 5 - Source Data 1 contain the numerical data used to generate the figures.

Article and author information

Author details

  1. Lei Liu

    Cellular Signaling Laboratory, International Research Center for Sensory Biology and Technology of MOST, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9824-9570
  2. Zhiran Fan

    Cellular Signaling Laboratory, International Research Center for Sensory Biology and Technology of MOST, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9543-1211
  3. Xavier Rovira

    MCS, Laboratory of Medicinal Chemistry, Institute for Advanced Chemistry of Catalonia (IQAC-CSIC), Spanish National Research Council, Barcelona, Spain
    For correspondence
    xavier.rovira@cid.csic.es
    Competing interests
    The authors declare that no competing interests exist.
  4. Li Xue

    Cellular Signaling Laboratory, International Research Center for Sensory Biology and Technology of MOST, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Salomé Roux

    Institut de Génomique Fonctionnelle, University of Montpellier, CNRS, INSERM, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6106-4863
  6. Isabelle Brabet

    Institut de Génomique Fonctionnelle, University of Montpellier, CNRS, INSERM, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Mingxia Xin

    Cellular Signaling Laboratory, International Research Center for Sensory Biology and Technology of MOST, Huazhong University of Science and Technology, Wuhan, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Jean-Philippe Pin

    Institut de Génomique Fonctionnelle, University of Montpellier, CNRS, INSERM, Montpellier, France
    For correspondence
    jean-philippe.pin@igf.cnrs.fr
    Competing interests
    The authors declare that no competing interests exist.
  9. Philippe Rondard

    Institut de Génomique Fonctionnelle, University of Montpellier, CNRS, INSERM, Montpellier, France
    For correspondence
    philippe.rondard@igf.cnrs.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1134-2738
  10. Jianfeng Liu

    Cellular Signaling Laboratory, International Research Center for Sensory Biology and Technology of MOST, Huazhong University of Science and Technology, Wuhan, China
    For correspondence
    jfliu@mail.hust.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0284-8377

Funding

Ministry of Science and Technology of the People's Republic of China (2018YFA0507003)

  • Jianfeng Liu

Agence Nationale de la Recherche (ANR-09-PIRI-0011)

  • Philippe Rondard

Fondation pour la recherche médicale FRM (FRM team: DEQ20170326522)

  • Jean-Philippe Pin

Spanish Ministry of Economy (SAF2015-74132-JIN)

  • Xavier Rovira

National Natural Science Foundation of China (81720108031)

  • Jianfeng Liu

National Natural Science Foundation of China (81872945)

  • Jianfeng Liu

National Natural Science Foundation of China (31721002)

  • Jianfeng Liu

National Natural Science Foundation of China (31420103909)

  • Jianfeng Liu

Ministry of Education of the People's Republic of China (B08029)

  • Jianfeng Liu

Centre National de la Recherche Scientifique (PICS n{degree sign}07030)

  • Philippe Rondard

Centre National de la Recherche Scientifique (PRC n{degree sign}1403)

  • Philippe Rondard

Institut National de la Santé et de la Recherche Médicale (IRP Brain Signal)

  • Philippe Rondard

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Andrew C Kruse, Harvard Medical School, United States

Version history

  1. Received: May 9, 2021
  2. Accepted: December 2, 2021
  3. Accepted Manuscript published: December 6, 2021 (version 1)
  4. Accepted Manuscript updated: December 10, 2021 (version 2)
  5. Version of Record published: December 23, 2021 (version 3)

Copyright

© 2021, Liu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,699
    Page views
  • 346
    Downloads
  • 10
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Lei Liu
  2. Zhiran Fan
  3. Xavier Rovira
  4. Li Xue
  5. Salomé Roux
  6. Isabelle Brabet
  7. Mingxia Xin
  8. Jean-Philippe Pin
  9. Philippe Rondard
  10. Jianfeng Liu
(2021)
Allosteric ligands control the activation of a class C GPCR heterodimer by acting at the transmembrane interface
eLife 10:e70188.
https://doi.org/10.7554/eLife.70188

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Daniel Muñoz-Reyes, Levi J McClelland ... Maria Jose Sanchez-Barrena
    Research Article

    The Neuronal Calcium Sensor 1, an EF-hand Ca2+ binding protein, and Ric-8A coregulate synapse number and probability of neurotransmitter release. Recently, the structures of Ric-8A bound to Ga have revealed how Ric-8A phosphorylation promotes Ga recognition and activity as a chaperone and guanine nucleotide exchange factor. However, the molecular mechanism by which NCS-1 regulates Ric-8A activity and its interaction with Ga subunits is not well understood. Given the interest in the NCS-1/Ric-8A complex as a therapeutic target in nervous system disorders, it is necessary to shed light on this molecular mechanism of action at atomic level. We have reconstituted NCS-1/Ric-8A complexes to conduct a multimodal approach and determine the sequence of Ca2+ signals and phosphorylation events that promote the interaction of Ric-8A with Ga. Our data show that the binding of NCS-1 and Ga to Ric-8A are mutually exclusive. Importantly, NCS-1 induces a structural rearrangement in Ric-8A that traps the protein in a conformational state that is inaccessible to Casein Kinase II-mediated phosphorylation, demonstrating one aspect of its negative regulation of Ric-8A-mediated G-protein signaling. Functional experiments indicate a loss of Ric-8A GEF activity towards Ga when complexed with NCS-1, and restoration of nucleotide exchange activity upon increasing Ca2+ concentration. Finally, the high-resolution crystallographic data reported here define the NCS-1/Ric-8A interface and will allow the development of therapeutic synapse function regulators with improved activity and selectivity.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Riham Ayoubi, Joel Ryan ... Carl Laflamme
    Research Advance

    Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, have demonstrated that: (i) more than 50% of all antibodies failed in one or more applications, (ii) yet, ~50–75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and (iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.