Computational prediction of GPCR oligomerization

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Highlights

  • GPCR dimers are a dynamic species with a changing dimerization interface that shifts during receptor activation and inactivation.

  • Computational methodologies are a valuable means of extracting information from those few dimer structures that exist.

  • Ensemble-based computational simulations of TM helices can be used to predict GPCR dimer interfaces.

  • FMO, a quantum mechanically-informed approach, can be used to analyse the chemical nature of the interactions between TMs in a GPCR dimer.

There has been a recent and prolific expansion in the number of GPCR crystal structures being solved: in both active and inactive forms and in complex with ligand, with G protein and with each other. Despite this, there is relatively little experimental information about the precise configuration of GPCR oligomers during these different biologically relevant states. While it may be possible to identify the experimental conditions necessary to crystallize a GPCR preferentially in a specific structural conformation, computational approaches afford a potentially more tractable means of describing the probability of formation of receptor dimers and higher order oligomers. Ensemble-based computational methods based on structurally determined dimers, coupled with a computational workflow that uses quantum mechanical methods to analyze the chemical nature of the molecular interactions at a GPCR dimer interface, will generate the reproducible and accurate predictions needed to predict previously unidentified GPCR dimers and to inform future advances in our ability to understand and begin to precisely manipulate GPCR oligomers in biological systems. It may also provide information needed to achieve an increase in the number of experimentally determined oligomeric GPCR structures.

Introduction

GPCRs are “proteins with the patterns of design and malleability of structure required for discriminating between an extraordinary variety of chemical signals” [1]. GPCRs were believed for many years to function as monomeric proteins and it has only been through an increasing body of experimental evidence, demonstrating not only the existence but the physiological and functional relevance of GPCR oligomers, that both homodimerization and heterodimerization and the formation of higher order oligomers has come to be (somewhat reluctantly) accepted by the GPCR field [2, 3, 4, 5].

The absence of structural data may have contributed to the long-standing belief in the monomeric nature of these cell surface receptor proteins. GPCRs have proved refractory to crystallization, relative to other protein classes, a difficulty that arises from the low conformational homogeneity of these signalling proteins and something that has only recently been resolved through the application of several innovative protein engineering techniques and crystallography methods [6, 7, 8, 9]. As a consequence, there has been a recent and prolific increase in the number of the GPCR structures in the Protein Data Bank (PDB) [10] and structural evidence for GPCR oligomers is now being added to the weight of evidence obtained from biological methods of studying GPCR oligomers in native cells, in tissues or in recombinant mammalian expression systems [11] to inform a holistic understanding of the nature of these signalling proteins.

Section snippets

Experimentally determined oligomeric GPCR structures

Ironically, now that we have unequivocally demonstrated the biological existence of GPCR homodimers and heterodimers and have successfully crystallized many members of this protein superfamily, it transpires that although there are over 300 solved GPCR structures [12], the overwhelming majority of these are, in fact, monomeric. Only 12 GPCR structures in PDB have a dimer present in the crystallographic asymmetric unit (i.e. dimers that were not generated by crystallographic symmetry) and

Computational approaches to GPCR oligomerization

The paucity of GPCR dimers and higher order oligomers in the PDB has prompted the use of computational modelling methods for the prediction of GPCR oligomers (e.g. see Refs. 11, 13, 14, 15, 16, 17, 18, 19). There are several caveats that need to be applied when interpreting results obtained with these approaches. Firstly, very few of the published studies involve performing a substantial number of replicas for each set of simulation conditions (summarized in Ref. 11). While such studies can

GPCR dimer interfaces

A number of computational studies have described GPCR dimer interfaces [18,19,20••,21,22,23,24,25, 26, 27, 28, 29, 30], many of these using inactive and active receptor models obtained from structurally determined dimers. Comparisons between these interfaces and those obtained from experiment have been made (see Refs. 31, 32, 33••) and several different and, potentially conflicting, results have been obtained. Interestingly, while these conflicts could arise from the caveats mentioned in

Identifying the molecular signature of GPCR dimer interfaces

In light of the increasing interest in identifying GPCR dimer interfaces, we have extended our previous studies to explore all pairwise combinations of A2A adenosine receptor TM helices and have identified interactions between TM1:TM2, TM4:TM4, the previously identified TM5:TM5 and TM6:TM6. TM1:TM2 is one of the dimer interfaces identified in Class A GPCRs and Figure 1 shows the TM1:TM2 interaction we have identified in the A2A receptor. There are 11 specific TM1:TM2 interactions identified for

Conclusions

GPCR dimers are a dynamic species with multiple forms and a changing dimerization interface that shifts during receptor activation and inactivation. The changes in the structure network and molecular signature of GPCRs during these processes are now beginning to be elucidated [46,47]. The computational characterization of TM helices allows the greatest flexibility in identifying all potential interfaces, providing rich information with which to interrogate experimental findings to identify GPCR

Conflict of interest statement

Nothing declared.

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgements

A.T.N. and A.H. are grateful for the support of the Biotechnology and Biological Sciences Research Council [grant number BB/P004245/1] and the EU H2020 CompBioMed project (http://www.compbiomed.eu/, 675451). N.A.A. was supported by a King Saud University Studentship. A.P. is supported by the London Interdisciplinary Bioscience PhD Consortium (LIDo) [grant number BB/M009513/1].

References (49)

  • M. Rodbell

    Signal transduction: evolution of an idea

    Biosci Rep

    (1995)
  • G. Milligan

    G protein-coupled receptor hetero-dimerization: contribution to pharmacology and function

    Br J Pharmacol

    (2009)
  • R. Jockers et al.

    G protein-coupled receptor oligomerization revisited: functional and pharmacological perspectives

    Pharmacol Rev

    (2014)
  • V.P. Jaakola et al.

    The 2.6 angstrom crystal structure of a human A2Aadenosine receptor bound to an antagonist

    Science (80-)

    (2008)
  • F. Magnani et al.

    Co-evolving stability and conformational homogeneity of the human adenosine A2a receptor

    Proc Natl Acad Sci U S A

    (2008)
  • B. Kobe et al.

    Fusion-protein-assisted protein crystallization

    Acta Crystallogr F Struct Biol Commun

    (2015)
  • J. Jiang et al.

    Protein Data Bank (PDB): database of three-dimensional structural information of biological macromolecules

    Acta Crystallogr D Struct Biol Commun

    (2002)
  • N.A. Altwaijry et al.

    An Ensemble-based protocol for the computational prediction of helix-helix interactions in G protein-coupled receptors using coarse-grained molecular dynamics

    J Chem Theory Comput

    (2017)
  • T.M. Tsonkov et al.

    GPCRdb in 2018: adding GPCR structure models and ligands

    Nucleic Acids Res

    (2017)
  • J. Selent et al.

    Oligomerization of G protein-coupled receptors: computational methods

    Curr Med Chem

    (2011)
  • X.-Y. Meng et al.

    Computational approaches for modeling GPCR dimerization

    Curr Pharm Biotechnol

    (2014)
  • S.A. Deshpande et al.

    Role of spatial inhomogenity in GPCR dimerisation predicted by receptor association-diffusion models

    Phys Biol

    (2017)
  • A.C. Schiedel et al.

    Prediction and targeting of interaction interfaces in G-protein coupled receptor oligomers

    Curr Top Med Chem

    (2018)
  • H. Guo et al.

    Methods used to study the oligomeric structure of G-protein-coupled receptors

    Biosci Rep

    (2017)
  • Cited by (0)

    3

    Present address: Biochemistry Department, College of Science, King Saud University, P.O. Box 2454, Riyadh 11451, Saudi Arabia.

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