Activation mechanism of the β2-adrenergic receptor

The dynamics of agonist-β2-adrenergic receptor activation induced by binding of GDP-bound Gs protein

There is considerable uncertainty about the mechanism by which the β₂-adrenergic receptor (β₂AR) is activated. Here we use molecular metadynamics computations to predict the mechanism by which an agonist induces the activation of the β₂AR and its cognate Gs protein. We found that binding agonist alone to the inactive β₂AR does not break the ionic lock and hence does not drive the β₂AR towards the activated conformation. However, we found that attaching the inactive Gs protein to the agonist-bound inactive β₂AR (containing the ionic lock) leads to partial insertion of Gαs-α5 into the core of β₂AR, which breaks the ionic lock, leading to activation of the Gs protein coupled to β₂AR. Upon activation, the Gαs protein undergoes a remarkable opening of the GDP binding pocket, making the GDP available for exchange or release. Concomitantly, Gαs-α5 undergoes a remarkable expansion in the β₂AR cytoplasmic region after the ionic lock is broken, inducing TM6 to displace outward by ~5 Å from TM3.

A subtle structural modification of a synthetic cannabinoid receptor agonist drastically increases its efficacy at the CB1 receptor

The emergence of synthetic cannabinoid receptor agonists (SCRAs) as illicit psychoactive substances has posed considerable public health risks that include fatalities. Many SCRAs exhibit much higher efficacy and potency, compared with the phytocannabinoid Δ9-tetrahydrocannabinol (THC), at the cannabinoid receptor 1 (CB1R), a G protein-coupled receptor involved in modulating neurotransmitter release. In this study, we investigated structure activity relationships (SAR) of aminoalkylindole SCRAs at CB1Rs, focusing on 5F-pentylindoles containing an amide linker attached to different head moieties. Using in vitro bioluminescence resonance energy transfer (BRET) assays, we identified a few of SCRAs exhibiting significantly higher efficacy in engaging the Gi protein and recruiting β-arrestin than the reference CB1R full agonist CP55940. Importantly, adding a methyl group at the head moiety of 5F-MMB-PICA yielded 5F-MDMB-PICA, an agonist exhibiting a large increase in efficacy and potency at the CB1R. This pharmacological observation was supported by a functional assay of the effects of these SCRAs on glutamate field potentials recorded in hippocampal slices. Molecular modeling and simulations of the CB1R bound with either of the SCRAs revealed critical structural determinants contributing to the higher efficacy of 5F-MDMB-PICA, and how these subtle differences propagated to the receptor-G protein interface. Thus, we find that apparently minor structural changes in the head moiety of SCRAs can cause major changes in efficacy. Our results highlight the need for close monitoring of structural modifications of newly emerging SCRAs and their potential for toxic drug responses in humans.

Stabilization of pre-existing neurotensin receptor conformational states by β-arrestin-1 and the biased allosteric modulator ML314

The neurotensin receptor 1 (NTS1) is a G protein-coupled receptor (GPCR) with promise as a drug target for the treatment of pain, schizophrenia, obesity, addiction, and various cancers. A detailed picture of the NTS1 structural landscape has been established by X-ray crystallography and cryo-EM and yet, the molecular determinants for why a receptor couples to G protein versus arrestin transducers remain poorly defined. We used 13CεH3-methionine NMR spectroscopy to show that binding of phosphatidylinositol-4,5-bisphosphate (PIP2) to the receptor's intracellular surface allosterically tunes the timescale of motions at the orthosteric pocket and conserved activation motifs - without dramatically altering the structural ensemble. β-arrestin-1 further remodels the receptor ensemble by reducing conformational exchange kinetics for a subset of resonances, whereas G protein coupling has little to no effect on exchange rates. A β-arrestin biased allosteric modulator transforms the NTS1:G protein complex into a concatenation of substates, without triggering transducer dissociation, suggesting that it may function by stabilizing signaling incompetent G protein conformations such as the non-canonical state. Together, our work demonstrates the importance of kinetic information to a complete picture of the GPCR activation landscape.

Pharmacological hallmarks of allostery at the M4 muscarinic receptor elucidated through structure and dynamics

Allosteric modulation of G protein-coupled receptors (GPCRs) is a major paradigm in drug discovery. Despite decades of research, a molecular-level understanding of the general principles that govern the myriad pharmacological effects exerted by GPCR allosteric modulators remains limited. The M₄ muscarinic acetylcholine receptor (M₄ mAChR) is a validated and clinically relevant allosteric drug target for several major psychiatric and cognitive disorders. In this study, we rigorously quantified the affinity, efficacy, and magnitude of modulation of two different positive allosteric modulators, LY2033298 (LY298) and VU0467154 (VU154), combined with the endogenous agonist acetylcholine (ACh) or the high-affinity agonist iperoxo (Ipx), at the human M₄ mAChR. By determining the cryo-electron microscopy structures of the M₄ mAChR, bound to a cognate G_i1 protein and in complex with ACh, Ipx, LY298-Ipx, and VU154-Ipx, and applying molecular dynamics simulations, we determine key molecular mechanisms underlying allosteric pharmacology. In addition to delineating the contribution of spatially distinct binding sites on observed pharmacology, our findings also revealed a vital role for orthosteric and allosteric ligand-receptor-transducer complex stability, mediated by conformational dynamics between these sites, in the ultimate determination of affinity, efficacy, cooperativity, probe dependence, and species variability. There results provide a holistic framework for further GPCR mechanistic studies and can aid in the discovery and design of future allosteric drugs.

General Metadynamics Protocol To Simulate Activation/Deactivation of Class A GPCRs: Proof of Principle for the Serotonin Receptor

We present a generally applicable metadynamics protocol for characterizing the activation free-energy profiles of class A G-protein coupled receptors and a proof-of-principle study for the 5HT_1A-receptor. The almost universal A¹⁰⁰ activation index, which depends on five inter-helix distances, is used as the single collective variable in well-tempered multiple-walker metadynamics simulations. Here, we show free-energy profiles for the serotonin receptor as binary (apo-receptor + G-protein-α-subunit and receptor + ligand) and ternary complexes with two prototypical orthosteric ligands: the full agonist serotonin and the partial agonist aripiprazole. Our results are not only compatible with previously reported experimental and computational data, but they also allow differences between active and inactive conformations to be determined in unprecedented atomic detail, and with respect to the so-called microswitches that have been suggested as determinants of activation, giving insight into their role in the activation mechanism.

Distinct activation mechanisms regulate subtype selectivity of Cannabinoid receptors

Design of cannabinergic subtype selective ligands is challenging because of high sequence and structural similarities of cannabinoid receptors (CB₁ and CB₂). We hypothesize that the subtype selectivity of designed selective ligands can be explained by the ligand binding to the conformationally distinct states between cannabinoid receptors. Analysis of ~ 700 μs of unbiased simulations using Markov state models and VAMPnets identifies the similarities and distinctions between the activation mechanism of both receptors. Structural and dynamic comparisons of metastable intermediate states allow us to observe the distinction in the binding pocket volume change during CB₁ and CB₂ activation. Docking analysis reveals that only a few of the intermediate metastable states of CB₁ show high affinity towards CB₂ selective agonists. In contrast, all the CB₂ metastable states show a similar affinity for these agonists. These results mechanistically explain the subtype selectivity of these agonists by deciphering the activation mechanism of cannabinoid receptors.

Activity Map and Transition Pathways of G Protein-Coupled Receptor Revealed by Machine Learning

Approximately, one-third of all U.S. Food and Drug Administration approved drugs target G protein-coupled receptors (GPCRs). However, more knowledge of protein structure-activity correlation is required to improve the efficacy of the drugs targeting GPCRs. In this study, we developed a machine learning model to predict the activation state and activity level of the receptors with high prediction accuracy. Furthermore, we applied this model to thousands of molecular dynamics trajectories to correlate residue-level conformational changes of a GPCR to its activity level. Finally, the most probable transition pathway between activation states of a receptor can be identified using the state-activity information. In addition, with this model, we can associate the contribution of each amino acid to the activation process. Using this method, we can design drugs that mainly target principal amino acids driving the transition between activation states of GPCRs. Our advanced method is generalizable to all GPCR classes and provides mechanistic insight into the activation mechanism in the receptors.

Computational insights into ligand-induced G protein and β-arrestin signaling of the dopamine D1 receptor

The dopamine D1 receptor (D1R), is a class A G protein coupled-receptor (GPCR) which has been a promising drug target for psychiatric and neurological disorders such as Parkinson's disease (PD). Previous studies have suggested that therapeutic effects can be realized by targeting the β-arrestin signaling pathway of dopamine receptors, while overactivation of the G protein-dependent pathways leads to side effects, such as dyskinesias. Therefore, it is highly desirable to develop a D1R ligand that selectively regulates the β-arrestin pathway. Currently, most D1R agonists are signaling-balanced and stimulate both G protein and β-arrestin pathways, with a few reports of G protein biased ligands. However, identification and characterization of β-arrestin biased D1R agonists has been a challenge thus far. In this study, we implemented Gaussian accelerated molecular dynamics (GaMD) simulations to provide valuable computational insights into the possible underlying molecular mechanism of the different signaling properties of two catechol and two non-catechol D1R agonists that are either G protein biased or signaling-balanced. Dynamic network analysis further identified critical residues in the allosteric signaling network of D1R for each ligand at different conformational or binding states. Some of these residues are crucial for G protein or arrestin signals of GPCRs based on previous studies. Finally, we provided a molecular design strategy which can be utilized by medicinal chemists to develop potential β-arrestin biased D1R ligands. The proposed hypotheses are experimentally testable and can guide the development of safer and more effective medications for a variety of CNS disorders.

Elucidation of a dynamic interplay between a beta-2 adrenergic receptor, its agonist, and stimulatory G protein

G protein-coupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligand-induced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta-2 adrenergic receptor (β2AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (Gs). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to β2AR by Gs protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from β2AR and the conformational interconversions of Gs between closed and open conformations in the NE(+)-β2AR-Gs ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter Gs α subunit (Gsα) conformational transitions. Our simulations showed that the interdomain movement and the stacking of Gsα α1 and α5 helices are significant for increasing the distance between the Gsα and β2AR, which may indicate a partial dissociation of Gsα The distance increase commences when Gsα is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of β2AR interacting with Gsα, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCR-mediated modulation of G protein activation.

Molecular Dynamics Simulation and Pharmacoinformatic Integrated Analysis of Bioactive Phytochemicals from Azadirachta indica (Neem) to Treat Diabetes Mellitus

Diabetes mellitus is a chronic hormonal and metabolic disorder in which our body cannot generate necessary insulin or does not act in response to it, accordingly, ensuing in discordantly high blood sugar (glucose) levels. Diabetes mellitus can lead to systemic dysfunction in the multiorgan system, including cardiac dysfunction, severe kidney disease, lowered quality of life, and increased mortality risk from diabetic complications. To uncover possible therapeutic targets to treat diabetes mellitus, the in silico drug design technique is widely used, which connects the ligand molecules with target proteins to construct a protein-ligand network. To identify new therapeutic targets for type 2 diabetes mellitus, Azadirachta indica is subjected to phytochemical screening using in silico molecular docking, pharmacokinetic behavior analysis, and simulation-based molecular dynamic analysis. This study has analyzed around 63 phytochemical compounds, and the initial selection of the compounds was made by analyzing their pharmacokinetic properties by comparing them with Lipinski’s rule of 5. The selected compounds were subjected to molecular docking. The top four ligand compounds were reported along with the control drug nateglinide based on their highest negative molecular binding affinity. The protein-ligand interaction of selected compounds has been analyzed to understand better how compounds interact with the targeted protein structure. The results of the in silico analysis revealed that 7-Deacetyl-7-oxogedunin had the highest negative docking score of −8.9 Kcal/mol and also demonstrated standard stability in a 100 ns molecular dynamic simulation performed with insulin receptor ectodomain. It has been found that these substances may rank among the essential supplementary antidiabetic drugs for treating type 2 diabetes mellitus. It is suggested that more in vivo and in vitro research studies be carried out to support the conclusions drawn from this in silico research strategy.

Structural basis of odorant recognition by a human odorant receptor

Our sense of smell enables us to navigate a vast space of chemically diverse odour molecules. This task is accomplished by the combinatorial activation of approximately 400 odorant G protein-coupled receptors encoded in the human genome1-3. How odorants are recognized by odorant receptors remains unclear. Here we provide mechanistic insight into how an odorant binds to a human odorant receptor. Using cryo-electron microscopy, we determined the structure of the active human odorant receptor OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant-binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an odorant receptor. Molecular dynamics simulations demonstrate that propionate-induced conformational changes in extracellular loop 3 activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate odorant receptor, providing insight into how this large family of G protein-coupled receptors enables our olfactory sense.

All-Atom Molecular Dynamics Simulations Indicated the Involvement of a Conserved Polar Signaling Channel in the Activation Mechanism of the Type I Cannabinoid Receptor

The type I cannabinoid G protein-coupled receptor (CB1, GPCR) is an intensely investigated pharmacological target, owing to its involvement in numerous physiological functions as well as pathological processes such as cancers, neurodegenerative diseases, metabolic disorders and neuropathic pain. In order to develop modern medications that exert their effects through binding to the CB1 receptor, it is essential to understand the structural mechanism of activation of this protein. The pool of atomic resolution experimental structures of GPCRs has been expanding rapidly in the past decade, providing invaluable information about the function of these receptors. According to the current state of the art, the activity of GPCRs involves structurally distinct, dynamically interconverting functional states and the activation is controlled by a cascade of interconnecting conformational switches in the transmembrane domain. A current challenge is to uncover how different functional states are activated and what specific ligand properties are responsible for the selectivity towards those different functional states. Our recent studies of the μ-opioid and β₂-adrenergic receptors (MOP and β₂AR, respectively) revealed that the orthosteric binding pockets and the intracellular surfaces of these receptors are connected through a channel of highly conserved polar amino acids whose dynamic motions are in high correlation in the agonist- and G protein-bound active states. This and independent literature data led us to hypothesize that, in addition to consecutive conformational transitions, a shift of macroscopic polarization takes place in the transmembrane domain, which is furnished by the rearrangement of polar species through their concerted movements. Here, we examined the CB1 receptor signaling complexes utilizing microsecond scale, all-atom molecular dynamics (MD) simulations in order to see if our previous assumptions could be applied to the CB1 receptor too. Apart from the identification of the previously proposed general features of the activation mechanism, several specific properties of the CB1 have been indicated that could possibly be associated with the signaling profile of this receptor.

Ligands selectively tune the local and global motions of neurotensin receptor 1 (NTS1)

Nuclear magnetic resonance (NMR) studies have revealed that fast methyl sidechain dynamics can report on entropically-driven allostery. Yet, NMR applications have been largely limited to the super-microsecond motional regimes of G protein-coupled receptors (GPCRs). We use ¹³C^ε-methionine chemical shift-based global order parameters to test if ligands affect the fast dynamics of a thermostabilized GPCR, neurotensin receptor 1 (NTS₁). We establish that the NTS₁ solution ensemble includes substates with lifetimes on several, discrete timescales. The longest-lived states reflect those captured in agonist- and inverse agonist-bound crystal structures, separated by large energy barriers. We observe that the rapid fluctuations of individual methionine residues, superimposed on these long-lived states, respond collectively with the degree of fast, global dynamics correlating with ligand pharmacology. This approach lends confidence to interpreting spectra in terms of local structure and methyl dihedral angle geometry. The results suggest a role for sub-microsecond dynamics and conformational entropy in GPCR ligand discrimination.

Cryo-EM structures of orphan GPR21 signaling complexes

GPR21 is a class-A orphan G protein-coupled receptor (GPCR) and a potential therapeutic target for type 2 diabetes and other metabolic disorders. This receptor shows high basal activity in coupling to multiple G proteins in the absence of any known endogenous agonist or synthetic ligand. Here, we present the structures of ligand-free human GPR21 bound to heterotrimeric miniGs and miniG15 proteins, respectively. We identified an agonist-like motif in extracellular loop 2 (ECL2) that occupies the orthosteric pocket and promotes receptor activation. A side pocket that may be employed as a new ligand binding site was also uncovered. Remarkably, G protein binding is accommodated by a flexible cytoplasmic portion of transmembrane helix 6 (TM6) which adopts little or undetectable outward movement. These findings will enable the design of modulators for GPR21 for understanding its signal transduction and exploring opportunity for deorphanization.

Modelling altered signalling of G-protein coupled receptors in inflamed environment to advance drug design

We previously reported the successful design, synthesis and testing of the prototype opioid painkiller NFEPP that does not elicit adverse side effects. The design process of NFEPP was based on mathematical modelling of extracellular interactions between G-protein coupled receptors (GPCRs) and ligands, recognizing that GPCRs function differently under pathological versus healthy conditions. We now present an additional and novel stochastic model of GPCR function that includes intracellular dissociation of G-protein subunits and modulation of plasma membrane calcium channels and their dependence on parameters of inflamed and healthy tissue (pH, radicals). The model is validated against in vitro experimental data for the ligands NFEPP and fentanyl at different pH values and radical concentrations. We observe markedly reduced binding affinity and calcium channel inhibition for NFEPP at normal pH compared to lower pH, in contrast to the effect of fentanyl. For increasing radical concentrations, we find enhanced constitutive G-protein activation but reduced ligand binding affinity. Assessing the different effects, the results suggest that, compared to radicals, low pH is a more important determinant of overall GPCR function in an inflamed environment. Future drug design efforts should take this into account.

Thermodynamic architecture and conformational plasticity of GPCRs

G-protein-coupled receptors (GPCRs) are ubiquitous integral membrane proteins involved in diverse cellular signaling processes. Here, we carry out a large-scale ensemble thermodynamic study of 45 ligand-free GPCRs employing a structure-based statistical mechanical framework. We find that multiple partially structured states co-exist in the GPCR native ensemble, with the TM helices 1, 6 and 7 displaying varied folding status, and shaping the conformational landscape. Strongly coupled residues are anisotropically distributed, accounting for only 13% of the residues, illustrating that a large number of residues are inherently dynamic. Active-state GPCRs are characterized by reduced conformational heterogeneity with altered coupling-patterns distributed throughout the structural scaffold. In silico alanine-scanning mutagenesis reveals that extra- and intra-cellular faces of GPCRs are coupled thermodynamically, highlighting an exquisite structural specialization and the fluid nature of the intramolecular interaction network. The ensemble-based perturbation methodology presented here lays the foundation for understanding allosteric mechanisms and the effects of disease-causing mutations in GCPRs.

AlphaFold2 versus experimental structures: evaluation on G protein-coupled receptors

As important drug targets, G protein-coupled receptors (GPCRs) play pivotal roles in a wide range of physiological processes. Extensive efforts of structural biology have been made on the study of GPCRs. However, a large portion of GPCR structures remain unsolved due to structural instability. Recently, AlphaFold2 has been developed to predict structure models of many functionally important proteins including all members of the GPCR family. Herein we evaluated the accuracy of GPCR structure models predicted by AlphaFold2. We revealed that AlphaFold2 could capture the overall backbone features of the receptors. However, the predicted models and experimental structures were different in many aspects including the assembly of the extracellular and transmembrane domains, the shape of the ligand-binding pockets, and the conformation of the transducer-binding interfaces. These differences impeded the use of predicted structure models in the functional study and structure-based drug design of GPCRs, which required reliable high-resolution structural information.

A Guide to In Silico Drug Design

The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.

Metadynamics simulations leveraged by statistical analyses and artificial intelligence-based tools to inform the discovery of G protein-coupled receptor ligands

G Protein-Coupled Receptors (GPCRs) are a large family of membrane proteins with pluridimensional signaling profiles. They undergo ligand-specific conformational changes, which in turn lead to the differential activation of intracellular signaling proteins and the consequent triggering of a variety of biological responses. This conformational plasticity directly impacts our understanding of GPCR signaling and therapeutic implications, as do ligand-specific kinetic differences in GPCR-induced transducer activation/coupling or GPCR-transducer complex stability. High-resolution experimental structures of ligand-bound GPCRs in the presence or absence of interacting transducers provide important, yet limited, insights into the highly dynamic process of ligand-induced activation or inhibition of these receptors. We and others have complemented these studies with computational strategies aimed at characterizing increasingly accurate metastable conformations of GPCRs using a combination of metadynamics simulations, state-of-the-art algorithms for statistical analyses of simulation data, and artificial intelligence-based tools. This minireview provides an overview of these approaches as well as lessons learned from them towards the identification of conformational states that may be difficult or even impossible to characterize experimentally and yet important to discover new GPCR ligands.

Global insights into the fine tuning of human A2AAR conformational dynamics in a ternary complex with an engineered G protein viewed by NMR

G protein-coupled receptor (GPCR) conformational plasticity enables formation of ternary signaling complexes with intracellular proteins in response to binding extracellular ligands. We investigate the dynamic process of GPCR complex formation in solution with the human A2A adenosine receptor (A2AAR) and an engineered Gs protein, mini-Gs. 2D nuclear magnetic resonance (NMR) data with uniform stable isotope-labeled A2AAR enabled a global comparison of A2AAR conformations between complexes with an agonist and mini-Gs and with an agonist alone. The two conformations are similar and show subtle differences at the receptor intracellular surface, supporting a model whereby agonist binding alone is sufficient to populate a conformation resembling the active state. However, an A2AAR "hot spot" connecting the extracellular ligand-binding pocket to the intracellular surface is observed to be highly dynamic in the ternary complex, suggesting a mechanism for allosteric connection between the bound G protein and the drug-binding pocket involving structural plasticity of the "toggle switch" tryptophan.

Understanding the Dynamics of the Structural States of Cannabinoid Receptors and the Role of Different Modulators

The cannabinoid receptors CB1R and CB2R are members of the G protein-coupled receptor (GPCR) family. These receptors have recently come to light as possible therapeutic targets for conditions affecting the central nervous system. However, because CB1R is known to have psychoactive side effects, its potential as a drug target is constrained. Therefore, targeting CB2R has become the primary focus of recent research. Using various molecular modeling studies, we analyzed the active, inactive, and intermediate states of both CBRs in this study. We conducted in-depth research on the binding properties of various groups of cannabinoid modulators, including agonists, antagonists, and inverse agonists, with all of the different conformational states of the CBRs. The binding effects of these modulators were studied on various CB structural features, including the movement of the transmembrane helices, the volume of the binding cavity, the internal fluids, and the important GPCR properties. Then, using in vitro experiments and computational modeling, we investigated how vitamin E functions as a lipid modulator to influence THC binding. This comparative examination of modulator binding to CBRs provides significant insight into the mechanisms of structural alterations and ligand affinity, which can directly help in the rational design of selective modulators that target either CB1R or CB2R.

Pre-Training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding

The latest biological findings observe that the motionless "lock-and-key" theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However, the computational expenditure limits the growth of protein trajectory-related studies, thus hindering the possibility of supervised learning. A spatial-temporal pre-training method based on the modified equivariant graph matching networks, dubbed ProtMD which has two specially designed self-supervised learning tasks: atom-level prompt-based denoising generative task and conformation-level snapshot ordering task to seize the flexibility information inside molecular dynamics (MD) trajectories with very fine temporal resolutions is presented. The ProtMD can grant the encoder network the capacity to capture the time-dependent geometric mobility of conformations along MD trajectories. Two downstream tasks are chosen to verify the effectiveness of ProtMD through linear detection and task-specific fine-tuning. A huge improvement from current state-of-the-art methods, with a decrease of 4.3% in root mean square error for the binding affinity problem and an average increase of 13.8% in the area under receiver operating characteristic curve and the area under the precision-recall curve for the ligand efficacy problem is observed. The results demonstrate a strong correlation between the magnitude of conformation's motion in the 3D space and the strength with which the ligand binds with its receptor.

Multi-state modeling of G-protein coupled receptors at experimental accuracy

The family of G-protein coupled receptors (GPCRs) is one of the largest protein families in the human genome. GPCRs transduct chemical signals from extracellular to intracellular regions via a conformational switch between active and inactive states upon ligand binding. While experimental structures of GPCRs remain limited, high-accuracy computational predictions are now possible with AlphaFold2. However, AlphaFold2 only predicts one state and is biased toward either the active or inactive conformation depending on the GPCR class. Here, a multi-state prediction protocol is introduced that extends AlphaFold2 to predict either active or inactive states at very high accuracy using state-annotated templated GPCR databases. The predicted models accurately capture the main structural changes upon activation of the GPCR at the atomic level. For most of the benchmarked GPCRs (10 out of 15), models in the active and inactive states were closer to their corresponding activation state structures. Median RMSDs of the transmembrane regions were 1.12 Å and 1.41 Å for the active and inactive state models, respectively. The models were more suitable for protein-ligand docking than the original AlphaFold2 models and template-based models. Finally, our prediction protocol predicted accurate GPCR structures and GPCR-peptide complex structures in GPCR Dock 2021, a blind GPCR-ligand complex modeling competition. We expect that high accuracy GPCR models in both activation states will promote understanding in GPCR activation mechanisms and drug discovery for GPCRs. At the time, the new protocol paves the way towards capturing the dynamics of proteins at high-accuracy via machine-learning methods.

One class classification for the detection of β2 adrenergic receptor agonists using single-ligand dynamic interaction data

G protein-coupled receptors are involved in many biological processes, relaying the extracellular signal inside the cell. Signaling is regulated by the interactions between receptors and their ligands, it can be stimulated by agonists, or inhibited by antagonists or inverse agonists. The development of a new drug targeting a member of this family requires to take into account the pharmacological profile of the designed ligands in order to elicit the desired response. The structure-based virtual screening of chemical libraries may prioritize a specific class of ligands by combining docking results and ligand binding information provided by crystallographic structures. The performance of the method depends on the relevance of the structural data, in particular the conformation of the targeted site, the binding mode of the reference ligand, and the approach used to compare the interactions formed by the docked ligand with those formed by the reference ligand in the crystallographic structure. Here, we propose a new method based on the conformational dynamics of a single protein–ligand reference complex to improve the biased selection of ligands with specific pharmacological properties in a structure-based virtual screening exercise. Interactions patterns between a reference agonist and the receptor, here exemplified on the β2 adrenergic receptor, were extracted from molecular dynamics simulations of the agonist/receptor complex and encoded in graphs used to train a one-class machine learning classifier. Different conditions were tested: low to high affinity agonists, varying simulation duration, considering or ignoring hydrophobic contacts, and tuning of the classifier parametrization. The best models applied to post-process raw data from retrospective virtual screening obtained by docking of test libraries effectively filtered out irrelevant poses, discarding inactive and non-agonist ligands while identifying agonists. Taken together, our results suggest that consistency of the binding mode during the simulation is a key to the success of the method.

The Third Extracellular Loop of Mammalian Odorant Receptors Is Involved in Ligand Binding

Mammals recognize chemicals in the air via G protein-coupled odorant receptors (ORs). In addition to their orthosteric binding site, other segments of these receptors modulate ligand recognition. Focusing on human hOR1A1, which is considered prototypical of class II ORs, we used a combination of molecular modeling, site-directed mutagenesis, and in vitro functional assays. We showed that the third extracellular loop of ORs (ECL3) contributes to ligand recognition and receptor activation. Indeed, site-directed mutations in ECL3 showed differential effects on the potency and efficacy of both carvones, citronellol, and 2-nonanone.

Multiple pore lining residues modulate water permeability of GlpF

The water permeability of aquaporins (AQPs) varies by more than an order of magnitude even though the pore structure, geometry, as well as the channel lining residues are highly conserved. However, channel gating by pH, divalent ions or phosphorylation was only shown for a minority of AQPs. Structural and in silico indications of water flux modulation by flexible side chains of channel lining residues have not been experimentally confirmed yet. Hence, the aquaporin "open state" is still considered to be a continuously open pore with water molecules permeating in a single-file fashion. Using protein mutations outside the selectivity filter in the aqua(glycerol)facilitator GlpF of Escherichia coli we, to the best of our knowledge, for the first time, modulate the position of the highly conserved Arg in the selectivity filter. This in turn enhances or reduces the unitary water permeability of GlpF as shown in silico by molecular dynamics (MD) simulations and in vitro with purified and reconstituted GlpF. This finding suggests that AQP water permeability can indeed be regulated by lipid bilayer asymmetry and the transmembrane potential. Strikingly, our long-term MD simulations reveal that not only the conserved Arg in the selectivity filter, but the position and dynamics of multiple other pore lining residues modulate water passage through GlpF. This finding is expected to trigger a wealth of future investigations on permeability and regulation of AQPs among others with the aim to tune water permeability for biotechnological applications.

β2 -Adrenoceptor agonist profiling reveals biased signalling phenotypes for the β2 -adrenoceptor with possible implications for the treatment of asthma

BACKGROUND AND PURPOSE

β-Adrenoceptor agonists relieve airflow obstruction by activating β2 -adrenoceptors, which are G protein-coupled receptors (GPCRs) expressed on human airway smooth muscle (HASM) cells. The currently available β-adrenoceptor agonists are balanced agonists, however, and signal through both the stimulatory G protein (Gs )- and β-arrestin-mediated pathways. While Gs signalling is beneficial and promotes HASM relaxation, β-arrestin activation is associated with reduced Gs efficacy. In this context, biased ligands that selectively promote β2 -adrenoceptor coupling to Gs signalling represent a promising strategy to treat asthma. Here, we examined several β-adrenoceptor agonists to identify Gs -biased ligands devoid of β-arrestin-mediated effects.

EXPERIMENTAL APPROACH

Gs -biased ligands for the β2 -adrenoceptor were identified by high-throughput screening and then evaluated for Gs interaction, Gi interaction, cAMP production, β-arrestin interaction, GPCR kinase (GRK) phosphorylation of the receptor, receptor trafficking, ERK activation, and functional desensitization of the β2 -adrenoceptor.

KEY RESULTS

We identified ractopamine, dobutamine, and higenamine as Gs -biased agonists that activate the Gs /cAMP pathway upon β2 -adrenoceptor stimulation while showing minimal Gi or β-arrestin interaction. Furthermore, these compounds did not induce any receptor trafficking and had reduced GRK5-mediated phosphorylation of the β2 -adrenoceptor. Finally, we observed minimal physiological desensitization of the β2 -adrenoceptor in primary HASM cells upon treatment with biased agonists.

CONCLUSION AND IMPLICATIONS

Our work demonstrates that Gs -biased signalling through the β2 -adrenoceptor may prove to be an effective strategy to promote HASM relaxation in the treatment of asthma. Such biased compounds may also be useful in identifying the molecular mechanisms that determine biased signalling and in design of safer drugs.

A Journey through Diastereomeric Space: The Design, Synthesis, In Vitro and In Vivo Pharmacological Activity, and Molecular Modeling of Novel Potent Diastereomeric MOR Agonists and Antagonists

Four sets of diastereomeric C9-alkenyl 5-phenylmorphans, varying in the length of the C9-alkenyl chain, were designed to examine the effect of these spatially distinct ligands on opioid receptors. Functional activity was obtained by forskolin-induced cAMP accumulation assays and several compounds were examined in the [³⁵S]GTPgS assay and in an assay for respiratory depression. In each of the four sets, similarities and differences were observed dependent on the length of their C9-alkenyl chain and, most importantly, their stereochemistry. Three MOR antagonists were found to be as or more potent than naltrexone and, unlike naltrexone, none had MOR, KOR, or DOR agonist activity. Several potent MOR full agonists were obtained, and, of particular interest partial agonists were found that exhibited less respiratory depression than that caused by morphine. The effect of stereochemistry and the length of the C9-alkenyl chain was also explored using molecular modeling. The MOR antagonists were found to interact with the inactive (4DKL) MOR crystal structures and agonists were found to interact with the active (6DDF) MOR crystal structures. The comparison of their binding modes at the mouse MOR was used to gain insight into the structural basis for their stereochemically induced pharmacological differences.

L-DOPA and Droxidopa: From Force Field Development to Molecular Docking into Human β2-Adrenergic Receptor

The increasing interest in the molecular mechanism of the binding of different agonists and antagonists to β₂-adrenergic receptor (β₂AR) inactive and active states has led us to investigate protein–ligand interactions using molecular docking calculations. To perform this study, the 3.2 Å X-ray crystal structure of the active conformation of human β₂AR in the complex with the endogenous agonist adrenaline has been used as a template for investigating the binding of two exogenous catecholamines to this adrenergic receptor. Here, we show the derivation of L-DOPA and Droxidopa OPLS all atom (AA) force field (FF) parameters via quantum mechanical (QM) calculations, molecular dynamics (MD) simulations in aqueous solutions of the two catecholamines and the molecular docking of both ligands into rigid and flexible β₂AR models. We observe that both ligands share with adrenaline similar experimentally observed binding anchor sites, which are constituted by Asp113/Asn312 and Ser203/Ser204/Ser207 side chains. Moreover, both L-DOPA and Droxidopa molecules exhibit binding affinities comparable to that predicted for adrenaline, which is in good agreement with previous experimental and computational results. L-DOPA and Droxidopa OPLS AA FFs have also been tested by performing MD simulations of these ligands docked into β₂AR proteins embedded in lipid membranes. Both hydrogen bonds and hydrophobic interaction networks observed over the 1 μs MD simulation are comparable with those derived from molecular docking calculations and MD simulations performed with the CHARMM FF.

Applications of Molecular Dynamics Simulation in Protein Study

Molecular Dynamics (MD) Simulations is increasingly used as a powerful tool to study protein structure-related questions. Starting from the early simulation study on the photoisomerization in rhodopsin in 1976, MD Simulations has been used to study protein function, protein stability, protein-protein interaction, enzymatic reactions and drug-protein interactions, and membrane proteins. In this review, we provide a brief review for the history of MD Simulations application and the current status of MD Simulations applications in protein studies.

Comprehensive analysis of a novel signature incorporating lipid metabolism and immune-related genes for assessing prognosis and immune landscape in lung adenocarcinoma

Background

As the crosstalk between metabolism and antitumor immunity continues to be unraveled, we aim to develop a prognostic gene signature that integrates lipid metabolism and immune features for patients with lung adenocarcinoma (LUAD).

Methods

First, differentially expressed genes (DEGs) related to lipid metabolism in LUAD were detected, and subgroups of LUAD patients were identified via the unsupervised clustering method. Based on lipid metabolism and immune-related DEGs, variables were determined by the univariate Cox and LASSO regression, and a prognostic signature was established. The prognostic value of the signature was evaluated by the Kaplan–Meier method, time-dependent ROC, and univariate and multivariate analyses. Five independent GEO datasets were employed for external validation. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis were performed to investigate the underlying mechanisms. The sensitivity to common chemotherapeutic drugs was estimated based on the GDSC database. Finally, we selected PSMC1 involved in the signature, which has not been reported in LUAD, for further experimental validation.

Results

LUAD patients with different lipid metabolism patterns exhibited significant differences in overall survival and immune infiltration levels. The prognostic signature incorporated 10 genes and stratified patients into high- and low-risk groups by median value splitting. The areas under the ROC curves were 0.69 (1-year), 0.72 (3-year), 0.74 (5-year), and 0.74 (10-year). The Kaplan–Meier survival analysis revealed a significantly poorer overall survival in the high-risk group in the TCGA cohort (p < 0.001). In addition, both univariate and multivariate Cox regression analyses indicated that the prognostic model was the individual factor affecting the overall survival of LUAD patients. Through GSEA and GSVA, we found that tumor progression and inflammatory and immune-related pathways were enriched in the high-risk group. Additionally, patients with high-risk scores showed higher sensitivity to chemotherapeutic drugs. The in vitro experiments further confirmed that PSMC1 could promote the proliferation and migration of LUAD cells.

Conclusions

We developed and validated a novel signature incorporating both lipid metabolism and immune-related genes for all-stage LUAD patients. This signature can be applied not only for survival prediction but also for guiding personalized chemotherapy and immunotherapy regimens.

Dynamic recognition of naloxone, morphine and endomorphin1 in the same pocket of µ-opioid receptors

Morphine, the most widely used analgesic, relieves severe pain by activating the μ-opioid receptor (MOR), whereas naloxone, with only slight structural changes compared to morphine, exhibits inhibitory effect, and is used to treat opioid abuse. The mechanism by which the MOR distinguishes between the two is unclear. Molecular dynamics (MD) simulations on a 1-μs time scale and metadynamics-enhanced conformational sampling are used here to determine the different interactions of these two ligands with MOR: morphine adjusted its pose by continuously flipping deeper into the pocket, whereas naloxone failed to penetrate deeper because its allyl group conflicts with several residues of MOR. The endogenous peptide ligand endomorphin-1 (EM-1) underwent almost no significant conformational changes during the MD simulations. To validate these processes, we employed GIRK4S143T, a MOR-activated Gβγ-protein effector, in combination with mutagenesis and electrophysiological recordings. We verified the role of some key residues in the dynamic recognition of naloxone and morphine and identified the key residue I322, which leads to differential recognition of morphine and naloxone while assisting EM-1 in activating MOR. Reducing the side chain size of I322 (MORI322A) transformed naloxone from an inhibitor directly into an agonist of MOR, and I322A also significantly attenuated the potency of MOR on EM-1, confirming that binding deep in the pocket is critical for the agonistic effect of MOR. This finding reveals a dynamic mechanism for the response of MOR to different ligands and provides a basis for the discovery of new ligands for MOR at the atomic level.

Examination of Intracellular GPCR-Mediated Signaling with High Temporal Resolution

The GTP-binding protein-coupled receptors (GPCRs) play important roles in physiology and neuronal signaling. More than a thousand genes, excluding the olfactory receptors, have been identified that encode these integral membrane proteins. Their pharmacological and functional properties make them fascinating targets for drug development, since various disease states can be treated and overcome by pharmacologically addressing these receptors and/or their downstream interacting partners. The activation of the GPCRs typically causes transient changes in the intracellular second messenger concentrations as well as in membrane conductance. In contrast to ion channel-mediated electrical signaling which results in spontaneous cellular responses, the GPCR-mediated metabotropic signals operate at a different time scale. Here we have studied the kinetics of two common GPCR-induced signaling pathways: (a) Ca2+ release from intracellular stores and (b) cyclic adenosine monophosphate (cAMP) production. The latter was monitored via the activation of cyclic nucleotide-gated (CNG) ion channels causing Ca2+ influx into the cell. Genetically modified and stably transfected cell lines were established and used in stopped-flow experiments to uncover the individual steps of the reaction cascades. Using two homologous biogenic amine receptors, either coupling to Go/q or Gs proteins, allowed us to determine the time between receptor activation and signal output. With ~350 ms, the release of Ca2+ from intracellular stores was much faster than cAMP-mediated Ca2+ entry through CNG channels (~6 s). The measurements with caged compounds suggest that this difference is due to turnover numbers of the GPCR downstream effectors rather than the different reaction cascades, per se.

A Statistical Journey through the Topological Determinants of the β2 Adrenergic Receptor Dynamics

Activation of G-protein-coupled receptors (GPCRs) is mediated by molecular switches throughout the transmembrane region of the receptor. In this work, we continued along the path of a previous computational study wherein energy transport in the β2 Adrenergic Receptor (β2-AR) was examined and allosteric switches were identified in the molecular structure through the reorganization of energy transport networks during activation. In this work, we further investigated the allosteric properties of β2-AR, using Protein Contact Networks (PCNs). In this paper, we report an extensive statistical analysis of the topological and structural properties of β2-AR along its molecular dynamics trajectory to identify the activation pattern of this molecular system. The results show a distinct character to the activation that both helps to understand the allosteric switching previously identified and confirms the relevance of the network formalism to uncover relevant functional features of protein molecules.

Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression

The development of therapeutic agonists for G protein-coupled receptors (GPCRs) is hampered by the propensity of GPCRs to couple to multiple intracellular signalling pathways. This promiscuous coupling leads to numerous downstream cellular effects, some of which are therapeutically undesirable. This is especially the case for adenosine A1 receptors (A1Rs) whose clinical potential is undermined by the sedation and cardiorespiratory depression caused by conventional agonists. We have discovered that the A1R-selective agonist, benzyloxy-cyclopentyladenosine (BnOCPA), is a potent and powerful analgesic but does not cause sedation, bradycardia, hypotension or respiratory depression. This unprecedented discrimination between native A1Rs arises from BnOCPA's unique and exquisitely selective activation of Gob among the six Gαi/o subtypes, and in the absence of β-arrestin recruitment. BnOCPA thus demonstrates a highly-specific Gα-selective activation of the native A1R, sheds new light on GPCR signalling, and reveals new possibilities for the development of novel therapeutics based on the far-reaching concept of selective Gα agonism.

Structure Prediction, Evaluation, and Validation of GPR18 Lipid Receptor Using Free Programs

The GPR18 receptor, often referred to as the N-arachidonylglycine receptor, although assigned (along with GPR55 and GPR119) to the new class A GPCR subfamily-lipid receptors, officially still has the status of a class A GPCR orphan. While its signaling pathways and biological significance have not yet been fully elucidated, increasing evidence points to the therapeutic potential of GPR18 in relation to immune, neurodegenerative, and cancer processes to name a few. Therefore, it is necessary to understand the interactions of potential ligands with the receptor and the influence of particular structural elements on their activity. Thus, given the lack of an experimentally solved structure, the goal of the present study was to obtain a homology model of the GPR18 receptor in the inactive state, meeting all requirements in terms of protein structure quality and recognition of active ligands. To increase the reliability and precision of the predictions, different contemporary protein structure prediction methods and software were used and compared herein. To test the usability of the resulting models, we optimized and compared the selected structures followed by the assessment of the ability to recognize known, active ligands. The stability of the predicted poses was then evaluated by means of molecular dynamics simulations. On the other hand, most of the best-ranking contemporary CADD software/platforms for its full usability require rather expensive licenses. To overcome this down-to-earth obstacle, the overarching goal of these studies was to test whether it is possible to perform the thorough CADD experiments with high scientific confidence while using only license-free/academic software and online platforms. The obtained results indicate that a wide range of freely available software and/or academic licenses allow us to carry out meaningful molecular modelling/docking studies.

Structures of β1-adrenergic receptor in complex with Gs and ligands of different efficacies

G-protein-coupled receptors (GPCRs) receive signals from ligands with different efficacies, and transduce to heterotrimeric G-proteins to generate different degrees of physiological responses. Previous studies revealed how ligands with different efficacies activate GPCRs. Here, we investigate how a GPCR activates G-proteins upon binding ligands with different efficacies. We report the cryo-EM structures of β1-adrenergic receptor (β1-AR) in complex with Gs (GαsGβ1Gγ2) and a partial agonist or a very weak partial agonist, and compare them to the β1-AR-Gs structure in complex with a full agonist. Analyses reveal similar overall complex architecture, with local conformational differences. Cellular functional studies with mutations of β1-AR residues show effects on the cellular signaling from β1-AR to the cAMP response initiated by the three different ligands, with residue-specific functional differences. Biochemical investigations uncover that the intermediate state complex comprising β1-AR and nucleotide-free Gs is more stable when binding a full agonist than a partial agonist. Molecular dynamics simulations support the local conformational flexibilities and different stabilities among the three complexes. These data provide insights into the ligand efficacy in the activation of GPCRs and G-proteins.

A cholesterol analog stabilizes the human β2-adrenergic receptor nonlinearly with temperature

In cell membranes, G protein-coupled receptors (GPCRs) interact with cholesterol, which modulates their assembly, stability, and conformation. Previous studies have shown how cholesterol modulates the structural properties of GPCRs at ambient temperature. Here, we characterized the mechanical, kinetic, and energetic properties of the human β2-adrenergic receptor (β2AR) in the presence and absence of the cholesterol analog cholesteryl hemisuccinate (CHS) at room temperature (25°C), at physiological temperature (37°C), and at high temperature (42°C). We found that CHS stabilized various structural regions of β2AR differentially, which changed nonlinearly with temperature. Thereby, the strongest effects were observed for structural regions that are important for receptor signaling. Moreover, at 37°C, but not at 25° or 42°C, CHS caused β2AR to increase and stabilize conformational substates to adopt to basal activity. These findings indicate that the nonlinear, temperature-dependent action of CHS in modulating the structural and functional properties of this GPCR is optimized for 37°C.

GPCR Intracellular Loop Regulation of Beta-Arrestin-Mediated Endosomal Signaling Dynamics

G protein-coupled receptors (GPCRs) are currently appreciated to be routed to diverse cellular platforms to generate both G protein-dependent and -independent signals. The latter has been best studied with respect to β-arrestin-associated receptor internalization and trafficking to signaling endosomes for extracellular signal-regulated kinase (ERK) activation. However, how GPCR structural and conformational variants regulate endosomal ERK signaling dynamics, which can be central in neural development, plasticity, and disease processes, is not well understood. Among class B GPCRs, the PACAP-selective PAC1 receptor is unique in the expression of variants that can contain intracellular loop 3 (ICL3) cassette inserts. The nervous system expresses preferentially the PAC1Null (no insert) and PAC1Hop (28-amino acid Hop insert) receptor variants. Our molecular modeling and signaling studies revealed that the PAC1Null and PAC1Hop receptor variants can associate with β-arrestin differentially, resulting in enhanced receptor internalization and ERK activation for the PAC1Hop variant. The study amplifies our understandings of GPCR intracellular loop structure/function relationships with the first example of how the duration of endosomal ERK activation can be guided by ICL3. The results provide a framework for how changes in GPCR variant expression can impact developmental and homeostatic processes and may be contributory to maladaptive neuroplasticity underlying chronic pain and stress-related disorders.

Delineating the conformational landscape and intrinsic properties of the angiotensin II type 2 receptor using a computational study

As a key regulator for the renin-angiotensin system, a class A G protein-coupled receptor (GPCR), AngII type 2 receptor (AT₂R), plays a pivotal role in the homeostasis of the cardiovascular system. Compared with other GPCRs, AT₂R has a unique antagonist-bound conformation and its mechanism is still an enigma. Here, we applied combined dynamic and evolutional approaches to investigate the conformational space and intrinsic properties of AT₂R. With molecular dynamic simulations, Markov State Models, and statistics coupled analysis, we captured the conformational landscape of AT₂R and identified its uniquity from both dynamical and evolutional viewpoints. A cryptic pocket was also discovered in the intermediate state during conformation transitions. These findings offer a deeper understanding of the AT₂R mechanism at an atomic level and provide hints for the design of novel AT₂R modulators.

Accelerating GPCR Drug Discovery With Conformation-Stabilizing VHHs

The human genome encodes 850 G protein-coupled receptors (GPCRs), half of which are considered potential drug targets. GPCRs transduce extracellular stimuli into a plethora of vital physiological processes. Consequently, GPCRs are an attractive drug target class. This is underlined by the fact that approximately 40% of marketed drugs modulate GPCRs. Intriguingly 60% of non-olfactory GPCRs have no drugs or candidates in clinical development, highlighting the continued potential of GPCRs as drug targets. The discovery of small molecules targeting these GPCRs by conventional high throughput screening (HTS) campaigns is challenging. Although the definition of success varies per company, the success rate of HTS for GPCRs is low compared to other target families (Fujioka and Omori, 2012; Dragovich et al., 2022). Beyond this, GPCR structure determination can be difficult, which often precludes the application of structure-based drug design approaches to arising HTS hits. GPCR structural studies entail the resource-demanding purification of native receptors, which can be challenging as they are inherently unstable when extracted from the lipid matrix. Moreover, GPCRs are flexible molecules that adopt distinct conformations, some of which need to be stabilized if they are to be structurally resolved. The complexity of targeting distinct therapeutically relevant GPCR conformations during the early discovery stages contributes to the high attrition rates for GPCR drug discovery programs. Multiple strategies have been explored in an attempt to stabilize GPCRs in distinct conformations to better understand their pharmacology. This review will focus on the use of camelid-derived immunoglobulin single variable domains (VHHs) that stabilize disease-relevant pharmacological states (termed ConfoBodies by the authors) of GPCRs, as well as GPCR:signal transducer complexes, to accelerate drug discovery. These VHHs are powerful tools for supporting in vitro screening, deconvolution of complex GPCR pharmacology, and structural biology purposes. In order to demonstrate the potential impact of ConfoBodies on translational research, examples are presented of their role in active state screening campaigns and structure-informed rational design to identify de novo chemical space and, subsequently, how such matter can be elaborated into more potent and selective drug candidates with intended pharmacology.

GPCR-mediated β-arrestin activation deconvoluted with single-molecule precision

β-arrestins bind G protein-coupled receptors to terminate G protein signaling and to facilitate other downstream signaling pathways. Using single-molecule fluorescence resonance energy transfer imaging, we show that β-arrestin is strongly autoinhibited in its basal state. Its engagement with a phosphopeptide mimicking phosphorylated receptor tail efficiently releases the β-arrestin tail from its N domain to assume distinct conformations. Unexpectedly, we find that β-arrestin binding to phosphorylated receptor, with a phosphorylation barcode identical to the isolated phosphopeptide, is highly inefficient and that agonist-promoted receptor activation is required for β-arrestin activation, consistent with the release of a sequestered receptor C tail. These findings, together with focused cellular investigations, reveal that agonism and receptor C-tail release are specific determinants of the rate and efficiency of β-arrestin activation by phosphorylated receptor. We infer that receptor phosphorylation patterns, in combination with receptor agonism, synergistically establish the strength and specificity with which diverse, downstream β-arrestin-mediated events are directed.

The mechanism for ligand activation of the GPCR-G protein complex

G protein–coupled receptors (GPCRs) activate cellular responses ranging from odorants to neurotransmitters. Binding an agonist leads to activation of a heterotrimeric G protein (GP) that stimulates external signaling. Unfortunately, the mechanism remains unknown. We show for 15 class A GPCRs, including opioids, adrenergics, adenosines, chemokines, muscarinics, cannabinoids, serotonins, and dopamines, that interaction of an inactive GP, including Gs, Gi, Go, G11, and Gq, to the inactive GPCR, containing the intracellular ionic lock between transmembrane (TM) helices 3 and 6, evolves exothermically to form a precoupled GPCR-GP complex with an opened TM3-TM6 and the GP-α5 helix partially inserted into the GPCR but not activated. We show that binding of agonist to this precoupled GPCR-GP complex causes the Gα protein to open into its active form, with the guanosine diphosphate exposed for signaling. This GP-first paradigm provides a strategy for developing selective agonists for GPCRs since it is the pharmacophore for the precoupled GPCR-GP complex that should be used to design drugs.

Activation and allosteric regulation of the orphan GPR88-Gi1 signaling complex

GPR88 is an orphan class A G-protein-coupled receptor that is highly expressed in the striatum and regulates diverse brain and behavioral functions. Here we present cryo-EM structures of the human GPR88-Gi1 signaling complex with or without a synthetic agonist (1R, 2R)-2-PCCA. We show that (1R, 2R)-2-PCCA is an allosteric modulator binding to a herein identified pocket formed by the cytoplasmic ends of transmembrane segments 5, 6, and the extreme C terminus of the α5 helix of Gi1. We also identify an electron density in the extracellular orthosteric site that may represent a putative endogenous ligand of GPR88. These structures, together with mutagenesis studies and an inactive state model obtained from metadynamics simulations, reveal a unique activation mechanism for GPR88 with a set of distinctive structure features and a water-mediated polar network. Overall, our results provide a structural framework for understanding the ligand binding, activation and signaling mechanism of GPR88, and will facilitate the innovative drug discovery for neuropsychiatric disorders and for deorphanization of this receptor.

A comprehensive evaluation of the potential binding poses of fentanyl and its analogs at the µ-opioid receptor

Fentanyl and its analogs are selective agonists of the µ-opioid receptor (MOR). Among novel synthetic opioids (NSOs), they dominate the recreational drug market and are the main culprits for the opioid crisis, which has been exacerbated by the COVID-19 pandemic. By taking advantage of the crystal structures of the MOR, several groups have investigated the binding mechanism of fentanyl, but have not reached a consensus, in terms of both the binding orientation and the fentanyl conformation. Thus, the binding mechanism of fentanyl at the MOR remains an unsolved and challenging question. Here, we carried out a systematic computational study to investigate the preferred fentanyl conformations, and how these conformations are being accommodated in the MOR binding pocket. We characterized the free energy landscape of fentanyl conformations with metadynamics simulations, and compared and evaluated several possible fentanyl binding conditions in the MOR with long-timescale molecular dynamics simulations. Our results indicate that the most preferred binding pose in the MOR binding pocket corresponds well with the global minimum on the energy landscape of fentanyl in the absence of the receptor, while the energy landscape can be reconfigured by modifying the fentanyl scaffold. The interactions with the receptor may stabilize a slightly unfavored fentanyl conformation in an alternative binding pose. By extending similar investigations to fentanyl analogs, our findings establish a structure–activity relationship of fentanyl binding at the MOR. In addition to providing a structural basis to understand the potential toxicity of the emerging NSOs, such insights will contribute to developing new, safer analgesics.

Activation Pathways of Neurotensin Receptor 1 Elucidated Using Statistical Machine Learning

Neurotensin receptor 1 (NTSR1) is a G-protein coupled receptor (GPCR) that mediates many biological processes through its interaction with the neurotensin (NTS) peptide. The NTSR1 protein is a clinically significant target as it is involved in the proliferation of cancer cells. Understanding the activation mechanism of NTSR1 is an important prerequisite for exploring the therapeutic potential of targeting NTSR1 and the development of drug molecules specific to NTSR1. Previous studies have been aimed at elucidating the structure of NTSR1 in the active and inactive conformations; however, the intermediate molecular pathway for NTSR1 activation dynamics is largely unknown. In this study, we performed extensive molecular dynamics (MD) simulations of the NTSR1 protein and analyzed its kinetic conformational changes to determine the microswitches that drive NTSR1 activation. To biophysically interpret the high-dimensional simulation trajectories, we used Markov state models and machine learning to elucidate the important and detailed conformational changes in NTSR1. Through the analysis of identified microswitches, we propose a mechanistic pathway for NTSR1 activation.

Binding and Activation of Serotonergic G-Protein Coupled Receptors by the Multimodal Antidepressant Vortioxetine

G-protein coupled receptors (GPCRs) are important pharmacological targets. Despite substantial progress, important questions still remain concerning the details of activation: how can a ligand act as an agonist in one receptor but as an antagonist in a homologous receptor, and how can agonists activate a receptor despite lacking polar functional groups able to interact with helix 5 as is the case for the related adrenergic receptors? Studying vortioxetine (VXT), an important multimodal antidepressant drug, may elucidate both questions. Herein, we present a thorough in silico analysis of VXT binding to 5-HT_1A, 5-HT_1B, and 5-HT₇ receptors and compare it with available experimental data. We are able to rationalize the differential mode of action of VXT at different receptors, but also, in the case of the 5-HT_1A receptor, we observe the initial steps of activation that inform about an activation mechanism that does not involve polar interaction with helix 5. The results extend our current understanding of agonist and antagonist action at aminergic GPCRs.