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