IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40045-y.html
   My bibliography  Save this article

GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach

Author

Listed:
  • Marin Matic

    (Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore)

  • Pasquale Miglionico

    (Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore)

  • Manae Tatsumi

    (Tohoku University)

  • Asuka Inoue

    (Tohoku University)

  • Francesco Raimondi

    (Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore)

Abstract

GPCRs are master regulators of cell signaling by transducing extracellular stimuli into the cell via selective coupling to intracellular G-proteins. Here we present a computational analysis of the structural determinants of G-protein-coupling repertoire of experimental and predicted 3D GPCR-G-protein complexes. Interface contact analysis recapitulates structural hallmarks associated with G-protein-coupling specificity, including TM5, TM6 and ICLs. We employ interface contacts as fingerprints to cluster Gs vs Gi complexes in an unsupervised fashion, suggesting that interface residues contribute to selective coupling. We experimentally confirm on a promiscuous receptor (CCKAR) that mutations of some of these specificity-determining positions bias the coupling selectivity. Interestingly, Gs-GPCR complexes have more conserved interfaces, while Gi/o proteins adopt a wider number of alternative docking poses, as assessed via structural alignments of representative 3D complexes. Binding energy calculations demonstrate that distinct structural properties of the complexes are associated to higher stability of Gs than Gi/o complexes. AlphaFold2 predictions of experimental binary complexes confirm several of these structural features and allow us to augment the structural coverage of poorly characterized complexes such as G12/13.

Suggested Citation

  • Marin Matic & Pasquale Miglionico & Manae Tatsumi & Asuka Inoue & Francesco Raimondi, 2023. "GPCRome-wide analysis of G-protein-coupling diversity using a computational biology approach," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40045-y
    DOI: 10.1038/s41467-023-40045-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40045-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-023-40045-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Patrick Bryant & Gabriele Pozzati & Arne Elofsson, 2022. "Author Correction: Improved prediction of protein-protein interactions using AlphaFold2," Nature Communications, Nature, vol. 13(1), pages 1-1, December.
    2. Javier García-Nafría & Rony Nehmé & Patricia C. Edwards & Christopher G. Tate, 2018. "Cryo-EM structure of the serotonin 5-HT1B receptor coupled to heterotrimeric Go," Nature, Nature, vol. 558(7711), pages 620-623, June.
    3. Patrick Bryant & Gabriele Pozzati & Arne Elofsson, 2022. "Improved prediction of protein-protein interactions using AlphaFold2," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Tilman Flock & Alexander S. Hauser & Nadia Lund & David E. Gloriam & Santhanam Balaji & M. Madan Babu, 2017. "Selectivity determinants of GPCR–G-protein binding," Nature, Nature, vol. 545(7654), pages 317-322, May.
    5. Hee Ryung Kim & Jun Xu & Shoji Maeda & Nguyen Minh Duc & Donghoon Ahn & Yang Du & Ka Young Chung, 2020. "Structural mechanism underlying primary and secondary coupling between GPCRs and the Gi/o family," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    6. Yanyong Kang & Oleg Kuybeda & Parker W. de Waal & Somnath Mukherjee & Ned Van Eps & Przemyslaw Dutka & X. Edward Zhou & Alberto Bartesaghi & Satchal Erramilli & Takefumi Morizumi & Xin Gu & Yanting Yi, 2018. "Cryo-EM structure of human rhodopsin bound to an inhibitory G protein," Nature, Nature, vol. 558(7711), pages 553-558, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andrew J. Y. Jones & Thomas H. Harman & Matthew Harris & Oliver E. Lewis & Graham Ladds & Daniel Nietlispach, 2024. "Binding kinetics drive G protein subtype selectivity at the β1-adrenergic receptor," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Li-Hua Zhao & Jingyu Lin & Su-Yu Ji & X. Edward Zhou & Chunyou Mao & Dan-Dan Shen & Xinheng He & Peng Xiao & Jinpeng Sun & Karsten Melcher & Yan Zhang & Xiao Yu & H. Eric Xu, 2022. "Structure insights into selective coupling of G protein subtypes by a class B G protein-coupled receptor," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Genki Hibi & Taro Shiraishi & Tatsuki Umemura & Kenji Nemoto & Yusuke Ogura & Makoto Nishiyama & Tomohisa Kuzuyama, 2023. "Discovery of type II polyketide synthase-like enzymes for the biosynthesis of cispentacin," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Kazutoshi Tani & Ryo Kanno & Xuan-Cheng Ji & Itsusei Satoh & Yuki Kobayashi & Malgorzata Hall & Long-Jiang Yu & Yukihiro Kimura & Akira Mizoguchi & Bruno M. Humbel & Michael T. Madigan & Zheng-Yu Wang, 2023. "Rhodobacter capsulatus forms a compact crescent-shaped LH1–RC photocomplex," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Jia Duan & Dan-Dan Shen & Tingting Zhao & Shimeng Guo & Xinheng He & Wanchao Yin & Peiyu Xu & Yujie Ji & Li-Nan Chen & Jinyu Liu & Huibing Zhang & Qiufeng Liu & Yi Shi & Xi Cheng & Hualiang Jiang & H., 2022. "Molecular basis for allosteric agonism and G protein subtype selectivity of galanin receptors," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Yang Yang & Hye Jin Kang & Ruogu Gao & Jingjing Wang & Gye Won Han & Jeffrey F. DiBerto & Lijie Wu & Jiahui Tong & Lu Qu & Yiran Wu & Ryan Pileski & Xuemei Li & Xuejun Cai Zhang & Suwen Zhao & Terry K, 2023. "Structural insights into the human niacin receptor HCA2-Gi signalling complex," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Andreas Lackner & Michael Müller & Magdalena Gamperl & Delyana Stoeva & Olivia Langmann & Henrieta Papuchova & Elisabeth Roitinger & Gerhard Dürnberger & Richard Imre & Karl Mechtler & Paulina A. Lato, 2023. "The Fgf/Erf/NCoR1/2 repressive axis controls trophoblast cell fate," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    8. Patrick Bryant & Gabriele Pozzati & Wensi Zhu & Aditi Shenoy & Petras Kundrotas & Arne Elofsson, 2022. "Predicting the structure of large protein complexes using AlphaFold and Monte Carlo tree search," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    9. Qianqiao Liu & Beth M. Stadtmueller, 2023. "SIgA structures bound to Streptococcus pyogenes M4 and human CD89 provide insights into host-pathogen interactions," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    10. Brooke M. Britton & Remy A. Yovanno & Sara F. Costa & Joshua McCausland & Albert Y. Lau & Jie Xiao & Zach Hensel, 2023. "Conformational changes in the essential E. coli septal cell wall synthesis complex suggest an activation mechanism," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    11. Patrick Bryant & Frank Noé, 2024. "Structure prediction of alternative protein conformations," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    12. Christoph Buhlheller & Theo Sagmeister & Christoph Grininger & Nina Gubensäk & Uwe B. Sleytr & Isabel Usón & Tea Pavkov-Keller, 2024. "SymProFold: Structural prediction of symmetrical biological assemblies," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    13. Hélène Bret & Jinmei Gao & Diego Javier Zea & Jessica Andreani & Raphaël Guerois, 2024. "From interaction networks to interfaces, scanning intrinsically disordered regions using AlphaFold2," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    14. Zhiye Guo & Jian Liu & Jeffrey Skolnick & Jianlin Cheng, 2022. "Prediction of inter-chain distance maps of protein complexes with 2D attention-based deep neural networks," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    15. Tânia F. Custódio & Maxime Killer & Dingquan Yu & Virginia Puente & Daniel P. Teufel & Alexander Pautsch & Gisela Schnapp & Marc Grundl & Jan Kosinski & Christian Löw, 2023. "Molecular basis of TASL recruitment by the peptide/histidine transporter 1, PHT1," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    16. Devlina Chakravarty & Joseph W. Schafer & Ethan A. Chen & Joseph F. Thole & Leslie A. Ronish & Myeongsang Lee & Lauren L. Porter, 2024. "AlphaFold predictions of fold-switched conformations are driven by structure memorization," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    17. Jae-Hyun Park & Kouki Kawakami & Naito Ishimoto & Tatsuya Ikuta & Mio Ohki & Toru Ekimoto & Mitsunori Ikeguchi & Dong-Sun Lee & Young-Ho Lee & Jeremy R. H. Tame & Asuka Inoue & Sam-Yong Park, 2023. "Structural basis for ligand recognition and signaling of hydroxy-carboxylic acid receptor 2," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    18. Mark J. Wall & Emily Hill & Robert Huckstepp & Kerry Barkan & Giuseppe Deganutti & Michele Leuenberger & Barbara Preti & Ian Winfield & Sabrina Carvalho & Anna Suchankova & Haifeng Wei & Dewi Safitri , 2022. "Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    19. Xuan Zhang & Guibing Liu & Ya-Ni Zhong & Ru Zhang & Chuan-Cheng Yang & Canyang Niu & Xuanyu Pu & Jingjing Sun & Tianyao Zhang & Lejin Yang & Chao Zhang & Xiu Li & Xinyuan Shen & Peng Xiao & Jin-Peng S, 2024. "Structural basis of ligand recognition and activation of the histamine receptor family," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    20. Jie Heng & Yunfei Hu & Guillermo Pérez-Hernández & Asuka Inoue & Jiawei Zhao & Xiuyan Ma & Xiaoou Sun & Kouki Kawakami & Tatsuya Ikuta & Jienv Ding & Yujie Yang & Lujia Zhang & Sijia Peng & Xiaogang N, 2023. "Function and dynamics of the intrinsically disordered carboxyl terminus of β2 adrenergic receptor," Nature Communications, Nature, vol. 14(1), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40045-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.