Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families

Searching the GPCR Heterodimer Network (GPCR-hetnet) Database for Information to Deduce the Receptor–Receptor Interface and Its Role in the Integrationof Receptor Heterodimer Functions

The G protein-coupled receptor heterocomplex network database (GPCR-hetnet) is a database designed to store information on GPCR heteroreceptor complexes and their allosteric receptor–receptor interactions. It is an expert-authored and peer-reviewed, curated collection of well-documented GPCR–GPCR interactions that span the gamut from classical GPCR–GPCR interactions to more complex receptor– receptor interactions (GPCR-Receptor Tyrosine Kinase and GPCR-ionotropic receptor/ligand gated ion channel). Although GPCR-hetnet contains interactions among GPCR from several different species, the curators have initially focused on receptor–receptor interactions in humans. Currently (August 2017) GPCR-hetnet contains information on 250 receptors (192 GPCR, 52 RTK, and 6 ionotropic receptors) and >1023 interactions. The GPCR-hetnet provides four searchable datasets: the hetnet, the non-hetnet, the rtknet, and the ionnet. Other supporting datasets include information about receptors that are present in GPCR-hetnet such as literature citations. This chapter describes in a basic protocol how to use, navigate, and browse through the GPCR-hetnet database to identify the clusters in which a receptor protomer of interest is involved, while further applicability are also described and introduced

MRI Assessment of Cardiomyopathy Induced by β1-Adrenoreceptor Autoantibodies and Protection Through β3-Adrenoreceptor Overexpression

The cardiopathogenic role of autoantibodies (aabs) directed against β1-adrenoreceptors (β1-AR) is well established. In mouse models, they cause progressive dilated cardiomyopathy (DCM) whose characterization with echocardiography requires prolonged protocols with numerous animals, complicating the evaluation of new treatments. Here, we report on the characterization of β1-aabs-induced DCM in mice using 11.7T MRI. C57BL/6J mice (n = 10 per group) were immunized against the β1-AR and left ventricular (LV) systolic function was assessed at 10, 18 and 27 weeks. Increase in LV mass/tibial length ratio was detected as the first modification at 10 weeks together with dilation of cavities, thereby outperforming echocardiography. Significant impairment in diastolic index was also observed in immunized animals before the onset of systolic dysfunction. Morphometric and histological measurements confirmed these observations. The same protocol performed on β3-AR-overexpressing mice and wild-type littermates (n = 8-12 per group) showed that transgenic animals were protected with reduced LV/TL ratio compared to wild-type animals and maintenance of the diastolic index. This study demonstrates that MRI allows a precocious detection of the subtle myocardial dysfunction induced by β1-aabs and that β3-AR stimulation blunts the development of β1-aabs-induced DCM, thereby paving the way for the use of β3AR-stimulating drugs to treat this autoimmune cardiomyopathy

Modeling GPCRs

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