Structural Mapping of Adenosine Receptor Mutations: Ligand Binding and Signaling Mechanisms

TrendsRecent technological advances in membrane protein crystallization have resulted in a nearly exponential increase of available receptor structures. The AR family is an important example in this respect. Crystal structures of antagonist- and agonist-bound adenosine A2A receptor have recently been supplemented by a fully activated conformation in complex with a G-protein mimic, and by antagonist bound structures of the A1 receptor.SDM experiments have been essential to identify residues involved in molecular interactions between ARs and their ligands. Leveraging on recent crystal structures, this vast amount of data can now be systematically classified and interconnected with chemical and structural information of ligands and receptors.The mapping of mutational data onto crystal structures provides new understanding of molecular interactions involved in ligand recognition. Together with computational modeling, this can be used as a roadmap to create novel hypotheses and assist in the design of more systematic mutagenesis studies to answer remaining structural and functional questions.The four adenosine receptors (ARs), A1, A2A, A2B, and A3, constitute a subfamily of G protein-coupled receptors (GPCRs) with exceptional foundations for structure-based ligand design. The vast amount of mutagenesis data, accumulated in the literature since the 1990s, has been recently supplemented with structural information, currently consisting of several inactive and active structures of the A2A and inactive conformations of the A1 ARs. We provide the first integrated view of the pharmacological, biochemical, and structural data available for this receptor family, by mapping onto the relevant crystal structures all site-directed mutagenesis data, curated and deposited at the GPCR database (available through http://www.gpcrdb.org). This analysis provides novel insights into ligand binding, allosteric modulation, and signaling of the AR family.Keywords: G protein-coupled receptor, adenosine receptor, mutagenesis, chemical modulationMedicinal Chemistr

Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors

The peptidergic system is the most abundant network of ligand-receptor-mediated signaling in humans. However, the physiological roles remain elusive for numerous peptides and more than 100 G protein-coupled receptors (GPCRs). Here we report the pairing of cognate peptides and receptors. Integrating comparative genomics across 313 species and bioinformatics on all protein sequences and structures of human class A GPCRs, we identify universal characteristics that uncover additional potential peptidergic signaling systems. Using three orthogonal biochemical assays, we pair 17 proposed endogenous ligands with five orphan GPCRs that are associated with diseases, including genetic, neoplastic, nervous and reproductive system disorders. We also identify additional peptides for nine receptors with recognized ligands and pathophysiological roles. This integrated computational and multifaceted experimental approach expands the peptide-GPCR network and opens the way for studies to elucidate the roles of these signaling systems in human physiology and disease. Video Abstract: Features learned from comparative sequence and structural analyses enabled prediction of peptide ligands for orphan GPCRs that, when coupled with functional validation, expose physiologically relevant signaling systems. © 2019 The Author(s

Community guidelines for GPCR ligand bias: IUPHAR review 32

GPCRs modulate a plethora of physiological processes and mediate the effects of one-third of FDA-approved drugs. Depending on which ligand activates a receptor, it can engage different intracellular transducers. This ‘biased signalling’ paradigm requires that we now characterize physiological signalling not just by receptors but by ligand–receptor pairs. Ligands eliciting biased signalling may constitute better drugs with higher efficacy and fewer adverse effects. However, ligand bias is very complex, making reproducibility and description challenging. Here, we provide guidelines and terminology for any scientists to design and report ligand bias experiments. The guidelines will aid consistency and clarity, as the basic receptor research and drug discovery communities continue to advance our understanding and exploitation of ligand bias. Scientific insight, biosensors, and analytical methods are still evolving and should benefit from and contribute to the implementation of the guidelines, together improving translation from in vitro to disease-relevant in vivo models