Computational prediction of GPCR oligomerization. (April 2019)

• Record Type: Journal Article
• Authors: Townsend-Nicholson, Andrea; Altwaijry, Nojood; Potterton, Andrew; Morao, Inaki; Heifetz, Alexander
• Is Part Of: Current opinion in structural biology. Volume 55(2019)
• Page Start: 178
• Page End: 184
• Publication Date: 2019-04
• Subjects: Molecular biology -- Periodicals; 570
• DOI: 10.1016/j.sbi.2019.04.005
• Languages: English
• ISSNs: 0959-440X

Abstract

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. Abstract : 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.