PlayMolecule Viewer: A Toolkit for the Visualization of Molecules and Other Data.

PlayMolecule Viewer is a web-based data visualization toolkit designed to streamline the exploration of data resulting from structural bioinformatics or computer-aided drug design efforts. By harnessing state-of-the-art web technologies such as WebAssembly, PlayMolecule Viewer integrates powerful Python libraries directly within the browser environment, which enhances its capabilities to manage multiple types of molecular data. With its intuitive interface, it allows users to easily upload, visualize, select, and manipulate molecular structures and associated data. The toolkit supports a wide range of common structural file formats and offers a variety of molecular representations to cater to different visualization needs. PlayMolecule Viewer is freely accessible at open.playmolecule.org, ensuring accessibility and availability to the scientific community and beyond.

In Silico Study of Allosteric Communication Networks in GPCR Signaling Bias.

Signaling bias is a promising characteristic of G protein-coupled receptors (GPCRs) as it provides the opportunity to develop more efficacious and safer drugs. This is because biased ligands can avoid the activation of pathways linked to side effects whilst still producing the desired therapeutic effect. In this respect, a deeper understanding of receptor dynamics and implicated allosteric communication networks in signaling bias can accelerate the research on novel biased drug candidates. In this review, we aim to provide an overview of computational methods and techniques for studying allosteric communication and signaling bias in GPCRs. This includes (i) the detection of allosteric communication networks and (ii) the application of network theory for extracting relevant information pipelines and highly communicated sites in GPCRs. We focus on the most recent research and highlight structural insights obtained based on the framework of allosteric communication networks and network theory for GPCR signaling bias.

SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions.

SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function.

Entrectinib-A SARS-CoV-2 Inhibitor in Human Lung Tissue (HLT) Cells.

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug.

Mechanistic insights into dopaminergic and serotonergic neurotransmission - concerted interactions with helices 5 and 6 drive the functional outcome.

Brain functions rely on neurotransmitters that mediate communication between billions of neurons. Disruption of this communication can result in a plethora of psychiatric and neurological disorders. In this work, we combine molecular dynamics simulations, live-cell biosensor and electrophysiological assays to investigate the action of the neurotransmitter dopamine at the dopaminergic D2 receptor (D2R). The study of dopamine and closely related chemical probes reveals how neurotransmitter binding translates into the activation of distinct subsets of D2R effectors (i.e.: Gi2, GoB, Gz and ß-arrestin 2). Ligand interactions with key residues in TM5 (S5.42) and TM6 (H6.55) in the D2R binding pocket yield a dopamine-like coupling signature, whereas exclusive TM5 interaction is typically linked to preferential G protein coupling (in particular GoB) over ß-arrestin. Further experiments for serotonin receptors indicate that the reported molecular mechanism is shared by other monoaminergic neurotransmitter receptors. Ultimately, our study highlights how sequence variation in position 6.55 is used by nature to fine-tune ß-arrestin recruitment and in turn receptor signaling and internalization of neurotransmitter receptors.

Structural dynamics bridge the gap between the genetic and functional levels of GPCRs.

G protein-coupled receptors (GPCRs) are implicated in nearly all physiological processes in the human body and represent an important drug targeting class. The genes encoding the different GPCR (sub)types determine their specific functionality, which can be altered by natural genetic variants and isoforms. Deciphering the molecular link between sequence diversity and its functional consequences is a current challenge and critical for the comprehension of the physiological response of GPCRs. It requires a global understanding of how protein sequence translates into protein structure, how this impacts the structural motions of the protein, and, finally, how all these factors determine the receptor functionality. Here, we discuss available resources and state-of-the-art computational approaches to address this question.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs.

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

GPCRmd uncovers the dynamics of the 3D-GPCRome.

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 three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over 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 for exploring 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, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.

Publisher Correction: GPCRmd uncovers the dynamics of the 3D-GPCRome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Synthesis, molecular modelling studies and biological evaluation of new oxoeicosanoid receptor 1 agonists.

The oxoeicosanoid receptor 1 (OXER1) is a member of the G-protein coupled receptors (GPCR) family, and is involved in inflammatory processes and oncogenesis. As such it is an attractive target for pharmacological intervention. The present study aimed to shed light on the molecular fundaments of OXER1 modulation using chemical probes structurally related to the natural agonist 5-oxo-ETE. In a first step, 5-oxo-ETE and its closely related derivatives (5-oxo-EPE and 4-oxo-DHA) were obtained by conducting concise and high-yielding syntheses. The biological activity of obtained compounds was assessed in terms of potency (EC50) and efficacy (Emax) for arrestin recruitment. Finally, molecular modelling and simulation were used to explore binding characteristics of 5-oxo-ETE and derivatives with the aim to rationalize biological activity. Our data suggest that the tested 5-oxo-ETE derivatives (i) insert quickly into the membrane, (ii) access the receptor via transmembrane helices (TMs) 5 and 6 from the membrane side and (iii) drive potency and efficacy by differential interaction with TM5 and 7. Most importantly, we found that the methyl ester of 5-oxo-ETE (1a) showed even a higher maximum response than the natural agonist (1). In contrast, shifting the 5-oxo group into position 4 results in inactive compounds (4-oxo DHA compounds (3) and (3a)). All in all, our study provides relevant structural data that help understanding better OXER1 functionality and its modulation. The structural information presented herein will be useful for designing new lead compounds with desired signalling profiles.

Membrane cholesterol effect on the 5-HT2A receptor: Insights into the lipid-induced modulation of an antipsychotic drug target.

The serotonin 5-hydroxytryptamine 2A (5-HT2A ) receptor is a G-protein-coupled receptor (GPCR) relevant for the treatment of CNS disorders. In this regard, neuronal membrane composition in the brain plays a crucial role in the modulation of the receptor functioning. Since cholesterol is an essential component of neuronal membranes, we have studied its effect on the 5-HT2A receptor dynamics through all-atom MD simulations. We find that the presence of cholesterol in the membrane increases receptor conformational variability in most receptor segments. Importantly, detailed structural analysis indicates that conformational variability goes along with the destabilization of hydrogen bonding networks not only within the receptor but also between receptor and lipids. In addition to increased conformational variability, we also find receptor segments with reduced variability. Our analysis suggests that this increased stabilization is the result of stabilizing effects of tightly bound cholesterol molecules to the receptor surface. Our finding contributes to a better understanding of membrane-induced alterations of receptor dynamics and points to cholesterol-induced stabilizing and destabilizing effects on the conformational variability of GPCRs.