G protein-coupled receptors (GPCRs) are the largest group of cell surface receptors in humans that signal in response to diverse inputs and regulate a plethora of cellular processes. Hence, they constitute one of the primary drug target classes. Progress in our understanding of GPCR dynamics, activation and signalling has opened new possibilities for selective drug development. A key advancement has been provided by the concept of biased agonism, which describes the ability of ligands acting at the same GPCR to elicit distinct cellular signalling profiles by preferentially stabilizing different active conformational states of the receptor. Application of this concept raises the prospect of 'designer' biased agonists as optimized therapeutics with improved efficacy and/or reduced side-effect profiles. However, this application will require a detailed understanding of the spectrum of drug actions and a structural understanding of the drug-receptor interactions that drive distinct pharmacologies. The recent revolution in GPCR structural biology provides unprecedented insights into ligand binding, conformational dynamics and the control of signalling outcomes. These insights, together with new approaches to multi-dimensional analysis of drug action, are allowing refined classification of drugs according to their pharmacodynamic profiles, which can be linked to receptor structure and predictions of preclinical drug efficacy.

Existing high-throughput methods to identify RNA-binding proteins (RBPs) involving capture of polyadenylated RNAs can not recover proteins that interact with non-adenylated RNAs, including lncRNA, pre-mRNA and bacterial RNAs. We present orthogonal organic phase separation (OOPS) which does not require molecular tagging or capture of polyadenylated RNA. We verify OOPS in HEK293, U2OS and MCF10A human cell lines, finding 96% of proteins recovered are bound to RNA. We demonstrate that all long RNAs can be crosslinked to proteins and recover 1838 RBPs, including 926 putative novel RBPs. Importantly, OOPS is approximately 100-fold more efficient than current techniques, enabling analysis of dynamic RNA-protein interactions. We identified 749 proteins with altered RNA binding following release from nocodazole arrest. Finally, OOPS allowed the characterisation of the first RNA-interactome for a bacterium, Escherichia coli. OOPS is an easy to use and flexible technique, compatible with downstream proteomics and RNA sequencing and applicable to any organism.

Cholesterol is a key component of cell membranes with a proven modulatory role on the function and ligand-binding properties of G-protein-coupled receptors (GPCRs). Crystal structures of prototypical GPCRs such as the adenosine A2A receptor (A2AR) have confirmed that cholesterol finds stable binding sites at the receptor surface suggesting an allosteric role of this lipid. Here we combine experimental and computational approaches to show that cholesterol can spontaneously enter the A2AR-binding pocket from the membrane milieu using the same portal gate previously suggested for opsin ligands. We confirm the presence of cholesterol inside the receptor by chemical modification of the A2AR interior in a biotinylation assay. Overall, we show that cholesterol's impact on A2AR-binding affinity goes beyond pure allosteric modulation and unveils a new interaction mode between cholesterol and the A2AR that could potentially apply to other GPCRs.

G protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new 3D molecular structures of GPCRs (3D-GPCRome) during the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique to explore the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyse and share GPCR MD data.GPCRmd originates from a community-driven effort to create the first open, interactive, and standardized database of GPCR MD simulations.However, static high-resolution structures provide little information on the intrinsic 71 flexibility of GPCRs, a key aspect to fully understand their function. Important advances 72