Positive allosteric mechanisms of adenosine A1 receptor-mediated analgesia.

The adenosine A1 receptor (A1R) is a promising therapeutic target for non-opioid analgesic agents to treat neuropathic pain1,2. However, development of analgesic orthosteric A1R agonists has failed because of a lack of sufficient on-target selectivity as well as off-tissue adverse effects3. Here we show that [2-amino-4-(3,5-bis(trifluoromethyl)phenyl)thiophen-3-yl)(4-chlorophenyl)methanone] (MIPS521), a positive allosteric modulator of the A1R, exhibits analgesic efficacy in rats in vivo through modulation of the increased levels of endogenous adenosine that occur in the spinal cord of rats with neuropathic pain. We also report the structure of the A1R co-bound to adenosine, MIPS521 and a Gi2 heterotrimer, revealing an extrahelical lipid-detergent-facing allosteric binding pocket that involves transmembrane helixes 1, 6 and 7. Molecular dynamics simulations and ligand kinetic binding experiments support a mechanism whereby MIPS521 stabilizes the adenosine-receptor-G protein complex. This study provides proof of concept for structure-based allosteric drug design of non-opioid analgesic agents that are specific to disease contexts.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

2-Aryladenine Derivatives as a Potent Scaffold for Adenosine Receptor Antagonists: The 6-Morpholino Derivatives.

A set of 2-aryl-9-H or methyl-6-morpholinopurine derivatives were synthesized and assayed through radioligand binding tests at human A1, A2A, A2B, and A3 adenosine receptor subtypes. Eleven purines showed potent antagonism at A1, A3, dual A1/A2A, A1/A2B, or A1/A3 adenosine receptors. Additionally, three compounds showed high affinity without selectivity for any specific adenosine receptor. The structure-activity relationships were made for this group of new compounds. The 9-methylpurine derivatives were generally less potent but more selective, and the 9H-purine derivatives were more potent but less selective. These compounds can be an important source of new biochemical tools and/or pharmacological drugs.

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.

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.

Northerly range expansion and first confirmed records of the smalltooth sand tiger shark, Odontaspis ferox, in the United Kingdom and Ireland.

Three Odontaspis ferox (confirmed by mtDNA barcoding) were found in the English Channel and Celtic Sea in 2023 at Lepe, UK (50.7846, -1.3508), Kilmore Quay, Ireland (52.1714, -6.5937), and Lyme Bay, UK (50.6448, -2.9302). These are the first records of O. ferox in either country, and extend the species' range by over three degrees of latitude, to >52° N. They were ~275 (female), 433 (female), and 293 cm (male) total length, respectively. These continue a series of new records, possibly indicative of a climate change-induced shift in the species' range.

Development and Characterization of Novel Selective, Non-Basic Dopamine D2 Receptor Antagonists for the Treatment of Schizophrenia.

The dopamine D2 receptor, which belongs to the family of G protein-coupled receptors (GPCR), is an important and well-validated drug target in the field of medicinal chemistry due to its wide distribution, particularly in the central nervous system, and involvement in the pathomechanism of many disorders thereof. Schizophrenia is one of the most frequent diseases associated with disorders in dopaminergic neurotransmission, and in which the D2 receptor is the main target for the drugs used. In this work, we aimed at discovering new selective D2 receptor antagonists with potential antipsychotic activity. Twenty-three compounds were synthesized, based on the scaffold represented by the D2AAK2 compound, which was discovered by our group. This compound is an interesting example of a D2 receptor ligand because of its non-classical binding to this target. Radioligand binding assays and SAR analysis indicated structural modifications of D2AAK2 that are possible to maintain its activity. These findings were further rationalized using molecular modeling. Three active derivatives were identified as D2 receptor antagonists in cAMP signaling assays, and the selected most active compound 17 was subjected to X-ray studies to investigate its stable conformation in the solid state. Finally, effects of 17 assessed in animal models confirmed its antipsychotic activity in vivo.

Design of Drug Efficacy Guided by Free Energy Simulations of the ß2 -Adrenoceptor.

G-protein-coupled receptors (GPCRs) play important roles in physiological processes and are modulated by drugs that either activate or block signaling. Rational design of the pharmacological efficacy profiles of GPCR ligands could enable the development of more efficient drugs, but is challenging even if high-resolution receptor structures are available. We performed molecular dynamics simulations of the ß2 adrenergic receptor in active and inactive conformations to assess if binding free energy calculations can predict differences in ligand efficacy for closely related compounds. Previously identified ligands were successfully classified into groups with comparable efficacy profiles based on the calculated shift in ligand affinity upon activation. A series of ligands were then predicted and synthesized, leading to the discovery of partial agonists with nanomolar potencies and novel scaffolds. Our results demonstrate that free energy simulations enable design of ligand efficacy and the same approach can be applied to other GPCR drug targets.

Ultralarge Virtual Screening Identifies SARS-CoV-2 Main Protease Inhibitors with Broad-Spectrum Activity against Coronaviruses.

Drugs targeting SARS-CoV-2 could have saved millions of lives during the COVID-19 pandemic, and it is now crucial to develop inhibitors of coronavirus replication in preparation for future outbreaks. We explored two virtual screening strategies to find inhibitors of the SARS-CoV-2 main protease in ultralarge chemical libraries. First, structure-based docking was used to screen a diverse library of 235 million virtual compounds against the active site. One hundred top-ranked compounds were tested in binding and enzymatic assays. Second, a fragment discovered by crystallographic screening was optimized guided by docking of millions of elaborated molecules and experimental testing of 93 compounds. Three inhibitors were identified in the first library screen, and five of the selected fragment elaborations showed inhibitory effects. Crystal structures of target-inhibitor complexes confirmed docking predictions and guided hit-to-lead optimization, resulting in a noncovalent main protease inhibitor with nanomolar affinity, a promising in vitro pharmacokinetic profile, and broad-spectrum antiviral effect in infected cells.

Potential origins of fish toti-like viruses in invertebrates.

The virus family Totiviridae had originally been considered to include only viruses which infected fungal and protist hosts, but since 2006 a growing number of viruses found in invertebrates and fish have been shown to cluster phylogenetically within this family. These Totiviridae-like, or toti-like, viruses do not appear to belong within any existing genera of Totiviridae, and whilst a number of new genus names have been suggested, none has yet been universally accepted. Within this growing number of toti-like viruses from animal hosts, there exists emerging viral threats particularly to aquaculture, namely Infectious myonecrosis virus in whiteleg shrimp and Piscine myocarditis virus (PMCV) in Atlantic salmon (Salmo salar). PMCV in particular continues to be an issue in salmon aquaculture as a number of questions remain unanswered about how the virus is transmitted and the route of entry into host fish. Using a phylogenetic approach, this study shows how PMCV and the other fish toti-like viruses probably have deeper origins in an arthropod host. Based on this, it is hypothesized that sea lice could be acting as a vector for PMCV, as seen with other RNA viruses in Atlantic salmon aquaculture and in the toti-like Cucurbit yellows-associated virus which is spread by the greenhouse whitefly Trialeurodes vaporariorum.

Can molecular dynamics simulations improve the structural accuracy and virtual screening performance of GPCR models?

The determination of G protein-coupled receptor (GPCR) structures at atomic resolution has improved understanding of cellular signaling and will accelerate the development of new drug candidates. However, experimental structures still remain unavailable for a majority of the GPCR family. GPCR structures and their interactions with ligands can also be modelled computationally, but such predictions have limited accuracy. In this work, we explored if molecular dynamics (MD) simulations could be used to refine the accuracy of in silico models of receptor-ligand complexes that were submitted to a community-wide assessment of GPCR structure prediction (GPCR Dock). Two simulation protocols were used to refine 30 models of the D3 dopamine receptor (D3R) in complex with an antagonist. Close to 60 µs of simulation time was generated and the resulting MD refined models were compared to a D3R crystal structure. In the MD simulations, the receptor models generally drifted further away from the crystal structure conformation. However, MD refinement was able to improve the accuracy of the ligand binding mode. The best refinement protocol improved agreement with the experimentally observed ligand binding mode for a majority of the models. Receptor structures with improved virtual screening performance, which was assessed by molecular docking of ligands and decoys, could also be identified among the MD refined models. Application of weak restraints to the transmembrane helixes in the MD simulations further improved predictions of the ligand binding mode and second extracellular loop. These results provide guidelines for application of MD refinement in prediction of GPCR-ligand complexes and directions for further method development.

Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity.

Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.

Structure-Guided Design of G-Protein-Coupled Receptor Polypharmacology.

Many diseases are polygenic and can only be treated efficiently with drugs that modulate multiple targets. However, rational design of compounds with multi-target profiles is rarely pursued because it is considered too difficult, in particular if the drug must enter the central nervous system. Here, a structure-based strategy to identify dual-target ligands of G-protein-coupled receptors is presented. We use this approach to design compounds that both antagonize the A2A adenosine receptor and activate the D2 dopamine receptor, which have excellent potential as antiparkinson drugs. Atomic resolution models of the receptors guided generation of a chemical library with compounds designed to occupy orthosteric and secondary binding pockets in both targets. Structure-based virtual screens identified ten compounds, of which three had affinity for both targets. One of these scaffolds was optimized to nanomolar dual-target activity and showed the predicted pharmacodynamic effect in a rat model of Parkinsonism.

Energy Landscapes Reveal Agonist Control of G Protein-Coupled Receptor Activation via Microswitches.

Agonist binding to G protein-coupled receptors (GPCRs) leads to conformational changes in the transmembrane region that activate cytosolic signaling pathways. Although high-resolution structures of different receptor states are available, atomistic details of allosteric signaling across the membrane remain elusive. We calculated free energy landscapes of ß2 adrenergic receptor activation using atomistic molecular dynamics simulations in an optimized string of swarms framework, which shed new light on how microswitches govern the equilibrium between conformational states. Contraction of the extracellular binding site in the presence of the agonist BI-167107 is obligatorily coupled to conformational changes in a connector motif located in the core of the transmembrane region. The connector is probabilistically coupled to the conformation of the intracellular region. An active connector promotes desolvation of a buried cavity, a twist of the conserved NPxxY motif, and an interaction between two conserved tyrosines in transmembrane helices 5 and 7 (Y-Y motif), which lead to a larger population of active-like states at the G protein binding site. This coupling is augmented by protonation of the strongly conserved Asp792.50. The agonist binding site hence communicates with the intracellular region via a cascade of locally connected microswitches. Characterization of these can be used to understand how ligands stabilize distinct receptor states and contribute to development drugs with specific signaling properties. The developed simulation protocol can likely be transferred to other class A GPCRs.

Scavenging of superoxide by a membrane-bound superoxide oxidase.

Superoxide is a reactive oxygen species produced during aerobic metabolism in mitochondria and prokaryotes. It causes damage to lipids, proteins and DNA and is implicated in cancer, cardiovascular disease, neurodegenerative disorders and aging. As protection, cells express soluble superoxide dismutases, disproportionating superoxide to oxygen and hydrogen peroxide. Here, we describe a membrane-bound enzyme that directly oxidizes superoxide and funnels the sequestered electrons to ubiquinone in a diffusion-limited reaction. Experiments in proteoliposomes and inverted membranes show that the protein is capable of efficiently quenching superoxide generated at the membrane in vitro. The 2.0 Å crystal structure shows an integral membrane di-heme cytochrome b poised for electron transfer from the P-side and proton uptake from the N-side. This suggests that the reaction is electrogenic and contributes to the membrane potential while also conserving energy by reducing the quinone pool. Based on this enzymatic activity, we propose that the enzyme family be denoted superoxide oxidase (SOO).

Nanopore whole genome sequencing and partitioned phylogenetic analysis supports a new salmonid alphavirus genotype (SAV7).

Salmon pancreas disease virus, more commonly known as salmonid alphavirus (SAV), is a single-stranded positive sense RNA virus and the causative agent of pancreas disease and sleeping disease in salmonids. In this study, a unique strain of SAV previously isolated from ballan wrasse was subjected to whole genome sequencing using nanopore sequencing. In order to accurately examine the evolutionary history of this strain in comparison to other SAV strains, a partitioned phylogenetic analysis was performed to account for variation in the rate of evolution for both individual genes and codon positions. Partitioning the genome alignments almost doubled the observed branch lengths in the phylogenetic tree when compared to the more common approach of applying one model of substitution across the genome and significantly increased the statistical fit of the best-fitting models of nucleotide substitution. Based on the genomic data, a valid case can be made for the viral strain examined in this study to be considered a new SAV genotype. In addition, this study adds to a growing number of studies in which SAV has been found to infect non-salmonid fish, and as such we have suggested that the viral species name be amended to the more inclusive 'piscine alphavirus'.

Genetic diversity of piscine myocarditis virus in Atlantic salmon Salmo salar L. in Ireland.

Piscine myocarditis virus (PMCV) is a double-stranded RNA virus which has been linked to cardiomyopathy syndrome (CMS) in Atlantic salmon (Salmo salar L.). The first recorded outbreak of CMS in Ireland occurred in 2012. Heart tissue samples were collected in the current study from farmed Atlantic salmon from various marine sites around Ireland, and the open reading frames (ORFs) 1 and 3 were amplified and sequenced in order to examine the genetic diversity of PMCV. Results showed PMCV to be largely homogenous in Irish samples, showing little genetic diversity. However, several amino acid positions within both ORF1 and ORF3 showed consistent variations unique to the Irish PMCV strains when compared with previously published Norwegian strains. The phylogeny generated in the present study suggests that PMCV may have been introduced into Ireland in two waves, both coming from the southern part of PMCV's range in Norway. In addition, over three-quarters of the PMCV strains which were sequenced came from fish not exhibiting any clinical signs of CMS, suggesting that either PMCV is evolving to become less virulent in Ireland or Irish Atlantic salmon are developing immunity to the disease.

Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks.

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

Role of aspartate 132 at the orifice of a proton pathway in cytochrome c oxidase.

Proton transfer across biological membranes underpins central processes in biological systems, such as energy conservation and transport of ions and molecules. In the membrane proteins involved in these processes, proton transfer takes place through specific pathways connecting the two sides of the membrane via control elements within the protein. It is commonly believed that acidic residues are required near the orifice of such proton pathways to facilitate proton uptake. In cytochrome c oxidase, one such pathway starts near a conserved Asp-132 residue. Results from earlier studies have shown that replacement of Asp-132 by, e.g., Asn, slows proton uptake by a factor of ∼5,000. Here, we show that proton uptake at full speed (∼10(4) s(-1)) can be restored in the Asp-132-Asn oxidase upon introduction of a second structural modification further inside the pathway (Asn-139-Thr) without compensating for the loss of the negative charge. This proton-uptake rate was insensitive to Zn(2+) addition, which in the wild-type cytochrome c oxidase slows the reaction, indicating that Asp-132 is required for Zn(2+) binding. Furthermore, in the absence of Asp-132 and with Thr at position 139, at high pH (>9), proton uptake was significantly accelerated. Thus, the data indicate that Asp-132 is not strictly required for maintaining rapid proton uptake. Furthermore, despite the rapid proton uptake in the Asn-139-Thr/Asp-132-Asn mutant cytochrome c oxidase, proton pumping was impaired, which indicates that the segment around these residues is functionally linked to pumping.

Molecular docking screening using agonist-bound GPCR structures: probing the A2A adenosine receptor.

Crystal structures of G protein-coupled receptors (GPCRs) have recently revealed the molecular basis of ligand binding and activation, which has provided exciting opportunities for structure-based drug design. The A2A adenosine receptor (A2AAR) is a promising therapeutic target for cardiovascular diseases, but progress in this area is limited by the lack of novel agonist scaffolds. We carried out docking screens of 6.7 million commercially available molecules against active-like conformations of the A2AAR to investigate whether these structures could guide the discovery of agonists. Nine out of the 20 predicted agonists were confirmed to be A2AAR ligands, but none of these activated the ARs. The difficulties in discovering AR agonists using structure-based methods originated from limited atomic-level understanding of the activation mechanism and a chemical bias toward antagonists in the screened library. In particular, the composition of the screened library was found to strongly reduce the likelihood of identifying AR agonists, which reflected the high ligand complexity required for receptor activation. Extension of this analysis to other pharmaceutically relevant GPCRs suggested that library screening may not be suitable for targets requiring a complex receptor-ligand interaction network. Our results provide specific directions for the future development of novel A2AAR agonists and general strategies for structure-based drug discovery.