G Protein-Coupled Receptor and Their Kinases in Cell Biology and Disease.

Over the past three decades, after Nobel prizes, Robert Lefkowitz and Brian Kobilka characterized G protein-coupled receptors (GPCRs) structure [...].

Receptor-Loaded Virion Endangers GPCR Signaling: Mechanistic Exploration of SARS-CoV-2 Infections and Pharmacological Implications.

SARS-CoV-2 exploits the respiratory tract epithelium including lungs as the primary entry point and reaches other organs through hematogenous expansion, consequently causing multiorgan injury. Viral E protein interacts with cell junction-associated proteins PALS1 or ZO-1 to gain massive penetration by disrupting the inter-epithelial barrier. Conversely, receptor-mediated viral invasion ensures limited but targeted infections in multiple organs. The ACE2 receptor represents the major virion loading site by virtue of its wide tissue distribution as demonstrated in highly susceptible lung, intestine, and kidney. In brain, NRP1 mediates viral endocytosis in a similar manner to ACE2. Prominently, PDZ interaction involves the entire viral loading process either outside or inside the host cells, whereas E, ACE2, and NRP1 provide the PDZ binding motif required for interacting with PDZ domain-containing proteins PALS1, ZO-1, and NHERF1, respectively. Hijacking NHERF1 and ß-arrestin by virion loading may impair specific sensory GPCR signalosome assembling and cause disordered cellular responses such as loss of smell and taste. PDZ interaction enhances SARS-CoV-2 invasion by supporting viral receptor membrane residence, implying that the disruption of these interactions could diminish SARS-CoV-2 infections and be another therapeutic strategy against COVID-19 along with antibody therapy. GPCR-targeted drugs are likely to alleviate pathogenic symptoms-associated with SARS-CoV-2 infection.

Exploring protein hotspots by optimized fragment pharmacophores.

Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.

FSC-Q: a CryoEM map-to-atomic model quality validation based on the local Fourier shell correlation.

In recent years, advances in cryoEM have dramatically increased the resolution of reconstructions and, with it, the number of solved atomic models. It is widely accepted that the quality of cryoEM maps varies locally; therefore, the evaluation of the maps-derived structural models must be done locally as well. In this article, a method for the local analysis of the map-to-model fit is presented. The algorithm uses a comparison of two local resolution maps. The first is the local FSC (Fourier shell correlation) between the full map and the model, while the second is calculated between the half maps normally used in typical single particle analysis workflows. We call the quality measure "FSC-Q", and it is a quantitative estimation of how much of the model is supported by the signal content of the map. Furthermore, we show that FSC-Q may be helpful to detect overfitting. It can be used to complement other methods, such as the Q-score method that estimates the resolvability of atoms.

Combining fragment docking with graph theory to improve ligand docking for homology model structures.

Computational protein-ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling). Here we introduce a fragment-based docking method and test if it reduces requirements on the accuracy of an input receptor structures relative to non-fragment docking approaches. In this method, small rigid fragments are docked first using AutoDock Vina to generate a large number of favorably docked poses spanning the receptor binding pocket. Then a graph theory maximum clique algorithm is applied to find combined sets of docked poses of different fragment types onto which the complete ligand can be properly aligned. On the basis of these alignments, possible binding poses of complete ligand are determined. This docking method is first tested for bound docking on a series of Cytochrome P450 (CYP450) enzyme-substrate complexes, in which experimentally determined receptor structures are used. For all complexes tested, ligand poses of less than 1 Å root mean square deviations (RMSD) from the actual binding positions can be recovered. Then the method is tested for unbound docking with modeled receptor structures for a number of protein-ligand complexes from different families including the very recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease. For all complexes, poses with RMSD less than 3 Å from actual binding positions can be recovered. Our results suggest that for docking with approximately modeled receptor structures, fragment-based methods can be more effective than common complete ligand docking approaches.

A review of antibody-based therapeutics targeting G protein-coupled receptors: an update.

INTRODUCTION: G protein-coupled receptors (GPCRs) play key roles in many biological functions and are linked to many diseases across all therapeutic areas. As such, GPCRs represent a significant opportunity for antibody-based therapeutics. AREAS COVERED: The structure of the major GPCR families is summarized in the context of choice of antigen source employed in the drug discovery process and receptor biology considerations which may impact on targeting strategies. An overview of the therapeutic GPCR-antibody target landscape and the diversity of current therapeutic programs is provided along with summary case studies for marketed antibody drugs or those in advanced clinical studies. Antibodies in early clinical studies and the emergence of next-generation modalities are also highlighted. EXPERT OPINION: The GPCR-antibody pipeline has progressed significantly with a number of technical developments enabling the successful resolution of some of the challenges previously encountered and this has contributed to the growing interest in antibody-based therapeutics addressing this target class.