Decoding the signaling of a GPCR heteromeric complex reveals a unifying mechanism of action of antipsychotic drugs.

Atypical antipsychotic drugs, such as clozapine and risperidone, have a high affinity for the serotonin 5-HT(2A) G protein-coupled receptor (GPCR), the 2AR, which signals via a G(q) heterotrimeric G protein. The closely related non-antipsychotic drugs, such as ritanserin and methysergide, also block 2AR function, but they lack comparable neuropsychological effects. Why some but not all 2AR inhibitors exhibit antipsychotic properties remains unresolved. We now show that a heteromeric complex between the 2AR and the G(i)-linked GPCR, metabotropic glutamate 2 receptor (mGluR2), integrates ligand input, modulating signaling output and behavioral changes. Serotonergic and glutamatergic drugs bind the mGluR2/2AR heterocomplex, which then balances Gi- and Gq-dependent signaling. We find that the mGluR2/2AR-mediated changes in Gi and Gq activity predict the psychoactive behavioral effects of a variety of pharmocological compounds. These observations provide mechanistic insight into antipsychotic action that may advance therapeutic strategies for disorders including schizophrenia and dementia.

GPCRmd uncovers the dynamics of the 3D-GPCRome.

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

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

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

De Novo Design of κ-Opioid Receptor Antagonists Using a Generative Deep-Learning Framework.

Likely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during periods of abstinence. Pharmacological blockade of the κ-opioid receptor (KOR) has been shown to abolish brain reward deficits in rodents during withdrawal, as well as to reduce the escalation of opioid use in rats with extended access to opioids. Although KOR antagonists represent promising candidates for the treatment of opioid addiction, very few potent selective KOR antagonists are known to date and most of them exhibit significant safety concerns. Here, we used a generative deep-learning framework for the de novo design of chemotypes with putative KOR antagonistic activity. Molecules generated by models trained with this framework were prioritized for chemical synthesis based on their predicted optimal interactions with the receptor. Our models and proposed training protocol were experimentally validated by binding and functional assays.

Predicted Mode of Binding to and Allosteric Modulation of the µ-Opioid Receptor by Kratom's Alkaloids with Reported Antinociception In Vivo.

Pain management devoid of serious opioid adverse effects is still far from reach despite vigorous research and development efforts. Alternatives to classical opioids have been sought for years, and mounting reports of individuals finding pain relief with kratom have recently intensified research on this natural product. Although the composition of kratom is complex, the pharmacological characterization of its most abundant alkaloids has drawn attention to three molecules in particular, owing to their demonstrated antinociceptive activity and limited side effects in vivo. These three molecules are mitragynine (MG), its oxidized active metabolite, 7-hydroxymitragynine (7OH), and the indole-to-spiropseudoindoxy rearrangement product of MG known as mitragynine pseudoindoxyl (MP). Although these three alkaloids have been shown to preferentially activate the G protein signaling pathway by binding and allosterically modulating the µ-opioid receptor (MOP), a molecular level understanding of this process is lacking and yet important for the design of improved therapeutics. The molecular dynamics study and experimental validation reported here provide an atomic level description of how MG, 7OH, and MP bind and allosterically modulate the MOP, which can eventually guide structure-based drug design of improved therapeutics.

Cryo-Electron Microscopy Structure of the αIIbß3-Abciximab Complex.

OBJECTIVE: The αIIbß3 antagonist antiplatelet drug abciximab is the chimeric antigen-binding fragment comprising the variable regions of murine monoclonal antibody 7E3 and the constant domains of human IgG1 and light chain κ. Previous mutagenesis studies suggested that abciximab binds to the ß3 C177-C184 specificity-determining loop (SDL) and Trp129 on the adjacent ß1-α1 helix. These studies could not, however, assess whether 7E3 or abciximab prevents fibrinogen binding by steric interference, disruption of either the αIIbß3-binding pocket for fibrinogen or the ß3 SDL (which is not part of the binding pocket but affects fibrinogen binding), or some combination of these effects. To address this gap, we used cryo-electron microscopy to determine the structure of the αIIbß3-abciximab complex at 2.8 Å resolution. Approach and Results: The interacting surface of abciximab is comprised of residues from all 3 complementarity-determining regions of both the light and heavy chains, with high representation of aromatic residues. Binding is primarily to the ß3 SDL and neighboring residues, the ß1-α1 helix, and ß3 residues Ser211, Val212 and Met335. Unexpectedly, the structure also indicated several interactions with αIIb. As judged by the cryo-electron microscopy model, molecular-dynamics simulations, and mutagenesis, the binding of abciximab does not appear to rely on the interaction with the αIIb residues and does not result in disruption of the fibrinogen-binding pocket; it does, however, compress and reduce the flexibility of the SDL. CONCLUSIONS: We deduce that abciximab prevents ligand binding by steric interference, with a potential contribution via displacement of the SDL and limitation of the flexibility of the SDL residues.

Mechanism of µ-Opioid Receptor-Magnesium Interaction and Positive Allosteric Modulation.

In the era of opioid abuse epidemics, there is an increased demand for understanding how opioid receptors can be allosterically modulated to guide the development of more effective and safer opioid therapies. Among the modulators of the µ-opioid (MOP) receptor, which is the pharmacological target for the majority of clinically used opioid drugs, are monovalent and divalent cations. Specifically, the monovalent sodium cation (Na+) has been known for decades to affect MOP receptor signaling by reducing agonist binding, whereas the divalent magnesium cation (Mg2+) has been shown to have the opposite effect, notwithstanding the presence of sodium chloride. Although ultra-high-resolution opioid receptor crystal structures have revealed a specific Na+ binding site and molecular dynamics (MD) simulation studies have supported the idea that this monovalent ion reduces agonist binding by stabilizing the receptor inactive state, the putative binding site of Mg2+ on the MOP receptor, as well as the molecular determinants responsible for its positive allosteric modulation of the receptor, are unknown. In this work, we carried out tens of microseconds of all-atom MD simulations to investigate the simultaneous binding of Mg2+ and Na+ cations to inactive and active crystal structures of the MOP receptor embedded in an explicit lipid-water environment and confirmed adequate sampling of Mg2+ ion binding with a grand canonical Monte Carlo MD method. Analyses of these simulations shed light on 1) the preferred binding sites of Mg2+ on the MOP receptor, 2) details of the competition between Mg2+ and Na+ cations for specific sites, 3) estimates of binding affinities, and 4) testable hypotheses of the molecular mechanism underlying the positive allosteric modulation of the MOP receptor by the Mg2+ cation.

Atomic-Level Characterization of the Methadone-Stabilized Active Conformation of µ-Opioid Receptor.

Methadone is a synthetic opioid agonist with notoriously unique properties, such as lower abuse liability and induced relief of withdrawal symptoms and drug cravings, despite acting on the same opioid receptors triggered by classic opioids-in particular the µ-opioid receptor (MOR). Its distinct pharmacologic properties, which have recently been attributed to the preferential activation of ß-arrestin over G proteins, make methadone a standard-of-care maintenance medication for opioid addiction. Although a recent biophysical study suggests that methadone stabilizes different MOR active conformations from those stabilized by classic opioid drugs or G protein-biased agonists, how this drug modulates the conformational equilibrium of MOR and what specific active conformation of the receptor it stabilizes are unknown. Here, we report the results of submillisecond adaptive sampling molecular dynamics simulations of a predicted methadone-bound MOR complex and compare them with analogous data obtained for the classic opioid morphine and the G protein-biased ligand TRV130. The model, which is supported by existing experimental data, is analyzed using Markov state models and transfer entropy analysis to provide testable hypotheses of methadone-specific conformational dynamics and activation kinetics of MOR. SIGNIFICANCE STATEMENT: Opioid addiction has reached epidemic proportions in both industrialized and developing countries. Although methadone maintenance treatment represents an effective therapeutic approach for opioid addiction, it is not as widely used as needed. In this study, we contribute an atomic-level understanding of how methadone exerts its unique function in pursuit of more accessible treatments for opioid addiction. In particular, we present details of a methadone-specific active conformation of the µ-opioid receptor that has thus far eluded experimental structural characterization.

Kinetic and thermodynamic insights into sodium ion translocation through the µ-opioid receptor from molecular dynamics and machine learning analysis.

The differential modulation of agonist and antagonist binding to opioid receptors (ORs) by sodium (Na+) has been known for decades. To shed light on the molecular determinants, thermodynamics, and kinetics of Na+ translocation through the µ-OR (MOR), we used a multi-ensemble Markov model framework combining equilibrium and non-equilibrium atomistic molecular dynamics simulations of Na+ binding to MOR active or inactive crystal structures embedded in an explicit lipid bilayer. We identify an energetically favorable, continuous ion pathway through the MOR active conformation only, and provide, for the first time: i) estimates of the energy differences and required timescales of Na+ translocation in inactive and active MORs, ii) estimates of Na+-induced changes to agonist binding validated by radioligand measurements, and iii) testable hypotheses of molecular determinants and correlated motions involved in this translocation, which are likely to play a key role in MOR signaling.

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors.

Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rates poses significant challenges, both computationally and experimentally. This is particularly palpable for complex systems like G Protein-Coupled Receptors (GPCRs) whose ligand unbinding typically requires very long timescales oftentimes inaccessible by standard molecular dynamics simulations. Enhanced sampling methods offer a useful alternative, and their efficiency can be further improved by using machine learning tools to identify optimal reaction coordinates. Here, we test the combination of two machine learning techniques, automatic mutual information noise omission and reweighted autoencoded variational Bayes for enhanced sampling, with infrequent metadynamics to efficiently study the unbinding kinetics of two classical drugs with different RTs in a prototypic GPCR, the µ-opioid receptor. Dissociation rates derived from these computations are within one order of magnitude from experimental values. We also use the simulation data to uncover the dissociation mechanisms of these drugs, shedding light on the structures of rate-limiting transition states, which, alongside metastable poses, are difficult to obtain experimentally but important to visualize when designing drugs with a desired kinetic profile.

Single Proteoliposome High-Content Analysis Reveals Differences in the Homo-Oligomerization of GPCRs.

G-protein-coupled receptors (GPCRs) control vital cellular signaling pathways. GPCR oligomerization is proposed to increase signaling diversity. However, many reports have arrived at disparate conclusions regarding the existence, stability, and stoichiometry of GPCR oligomers, partly because of cellular complexity and ensemble averaging of intrareconstitution heterogeneities that complicate the interpretation of oligomerization data. To overcome these limitations, we exploited fluorescence-microscopy-based high-content analysis of single proteoliposomes. This allowed multidimensional quantification of intrinsic monomer-monomer interactions of three class A GPCRs (ß2-adrenergic receptor, cannabinoid receptor type 1, and opsin). Using a billion-fold less protein than conventional assays, we quantified oligomer stoichiometries, association constants, and the influence of two ligands and membrane curvature on oligomerization, revealing key similarities and differences for three GPCRs with decidedly different physiological functions. The assays introduced here will assist with the quantitative experimental observation of oligomerization for transmembrane proteins in general.

Development of novel biosensors to study receptor-mediated activation of the G-protein α subunits Gs and Golf.

Gαs (Gs) and Gαolf (Golf) are highly homologous G-protein α subunits that activate adenylate cyclase, thereby serving as crucial mediators of intracellular signaling. Because of their dramatically different brain expression patterns, we studied similarities and differences between their activation processes with the aim of comparing their receptor coupling mechanisms. We engineered novel luciferase- and Venus-fused Gα constructs that can be used in bioluminescence resonance energy transfer assays. In conjunction with molecular simulations, these novel biosensors were used to determine receptor activation-induced changes in conformation. Relative movements in Gs were consistent with the crystal structure of ß2 adrenergic receptor in complex with Gs Conformational changes in Golf activation are shown to be similar to those in Gs Overall the current study reveals general similarities between Gs and Golf activation at the molecular level and provides a novel set of tools to search for Gs- and Golf-specific receptor pharmacology. In view of the wide functional and pharmacological roles of Gs- and Golf-coupled dopamine D1 receptor and adenosine A2A receptor in the brain and other organs, elucidating their differential structure-function relationships with Gs and Golf might provide new approaches for the treatment of a variety of neuropsychiatric disorders. In particular, these novel biosensors can be used to reveal potentially therapeutic dopamine D1 receptor and adenosine A2A receptor ligands with functionally selective properties between Gs and Golf signaling.

An efficient strategy to estimate thermodynamics and kinetics of G protein-coupled receptor activation using metadynamics and maximum caliber.

Computational strategies aimed at unveiling the thermodynamic and kinetic properties of G Protein-Coupled Receptor (GPCR) activation require extensive molecular dynamics simulations of the receptor embedded in an explicit lipid-water environment. A possible method for efficiently sampling the conformational space of such a complex system is metadynamics (MetaD) with path collective variables (CVs). Here, we applied well-tempered MetaD with path CVs to one of the few GPCRs for which both inactive and fully active experimental structures are available, the µ-opioid receptor (MOR), and assessed the ability of this enhanced sampling method to estimate the thermodynamic properties of receptor activation in line with those obtained by more computationally expensive adaptive sampling protocols. While n-body information theory analysis of these simulations confirmed that MetaD can efficiently characterize ligand-induced allosteric communication across the receptor, standard MetaD cannot be used directly to derive kinetic rates because transitions are accelerated by a bias potential. Applying the principle of Maximum Caliber (MaxCal) to the free-energy landscape of morphine-bound MOR reconstructed from MetaD, we obtained Markov state models that yield kinetic rates of MOR activation in agreement with those obtained by adaptive sampling. Taken together, these results suggest that the MetaD-MaxCal combination creates an efficient strategy for estimating the thermodynamic and kinetic properties of GPCR activation at an affordable computational cost.

Impact of Lipid Composition and Receptor Conformation on the Spatio-temporal Organization of µ-Opioid Receptors in a Multi-component Plasma Membrane Model.

The lipid composition of cell membranes has increasingly been recognized as playing an important role in the function of various membrane proteins, including G Protein-Coupled Receptors (GPCRs). For instance, experimental and computational evidence has pointed to lipids influencing receptor oligomerization directly, by physically interacting with the receptor, and/or indirectly, by altering the bulk properties of the membrane. While the exact role of oligomerization in the function of class A GPCRs such as the µ-opioid receptor (MOR) is still unclear, insight as to how these receptors oligomerize and the relevance of the lipid environment to this phenomenon is crucial to our understanding of receptor function. To examine the effect of lipids and different MOR conformations on receptor oligomerization we carried out extensive coarse-grained molecular dynamics simulations of crystal structures of inactive and/or activated MOR embedded in an idealized mammalian plasma membrane composed of 63 lipid types asymmetrically distributed across the two leaflets. The results of these simulations point, for the first time, to specific direct and indirect effects of the lipids, as well as the receptor conformation, on the spatio-temporal organization of MOR in the plasma membrane. While sphingomyelin-rich, high-order lipid regions near certain transmembrane (TM) helices of MOR induce an effective long-range attractive force on individual protomers, both long-range lipid order and interface formation are found to be conformation dependent, with a larger number of different interfaces formed by inactive MOR compared to active MOR.

How Oliceridine (TRV-130) Binds and Stabilizes a µ-Opioid Receptor Conformational State That Selectively Triggers G Protein Signaling Pathways.

Substantial attention has recently been devoted to G protein-biased agonism of the µ-opioid receptor (MOR) as an ideal new mechanism for the design of analgesics devoid of serious side effects. However, designing opioids with appropriate efficacy and bias is challenging because it requires an understanding of the ligand binding process and of the allosteric modulation of the receptor. Here, we investigated these phenomena for TRV-130, a G protein-biased MOR small-molecule agonist that has been shown to exert analgesia with less respiratory depression and constipation than morphine and that is currently being evaluated in human clinical trials for acute pain management. Specifically, we carried out multimicrosecond, all-atom molecular dynamics (MD) simulations of the binding of this ligand to the activated MOR crystal structure. Analysis of >50 µs of these MD simulations provides insights into the energetically preferred binding pathway of TRV-130 and its stable pose at the orthosteric binding site of MOR. Information transfer from the TRV-130 binding pocket to the intracellular region of the receptor was also analyzed, and was compared to a similar analysis carried out on the receptor bound to the classical unbiased agonist morphine. Taken together, these studies lead to a series of testable hypotheses of ligand-receptor interactions that are expected to inform the structure-based design of improved opioid analgesics.

Preferred supramolecular organization and dimer interfaces of opioid receptors from simulated self-association.

Substantial evidence in support of the formation of opioid receptor (OR) di-/oligomers suggests previously unknown mechanisms used by these proteins to exert their biological functions. In an attempt to guide experimental assessment of the identity of the minimal signaling unit for ORs, we conducted extensive coarse-grained (CG) molecular dynamics (MD) simulations of different combinations of the three major OR subtypes, i.e., µ-OR, δ-OR, and κ-OR, in an explicit lipid bilayer. Specifically, we ran multiple, independent MD simulations of each homomeric µ-OR/µ-OR, δ-OR/δ-OR, and κ-OR/κ-OR complex, as well as two of the most studied heteromeric complexes, i.e., δ-OR/µ-OR and δ-OR/κ-OR, to derive the preferred supramolecular organization and dimer interfaces of ORs in a cell membrane model. These simulations yielded over 250 microseconds of accumulated data, which correspond to approximately 1 millisecond of effective simulated dynamics according to established scaling factors of the CG model we employed. Analysis of these data indicates similar preferred supramolecular organization and dimer interfaces of ORs across the different receptor subtypes, but also important differences in the kinetics of receptor association at specific dimer interfaces. We also investigated the kinetic properties of interfacial lipids, and explored their possible role in modulating the rate of receptor association and in promoting the formation of filiform aggregates, thus supporting a distinctive role of the membrane in OR oligomerization and, possibly, signaling.

Inward-facing conformation of the zinc transporter YiiP revealed by cryoelectron microscopy.

YiiP is a dimeric Zn(2+)/H(+) antiporter from Escherichia coli belonging to the cation diffusion facilitator family. We used cryoelectron microscopy to determine a 13-Å resolution structure of a YiiP homolog from Shewanella oneidensis within a lipid bilayer in the absence of Zn(2+). Starting from the X-ray structure in the presence of Zn(2+), we used molecular dynamics flexible fitting to build a model consistent with our map. Comparison of the structures suggests a conformational change that involves pivoting of a transmembrane, four-helix bundle (M1, M2, M4, and M5) relative to the M3-M6 helix pair. Although accessibility of transport sites in the X-ray model indicates that it represents an outward-facing state, our model is consistent with an inward-facing state, suggesting that the conformational change is relevant to the alternating access mechanism for transport. Molecular dynamics simulation of YiiP in a lipid environment was used to address the feasibility of this conformational change. Association of the C-terminal domains is the same in both states, and we speculate that this association is responsible for stabilizing the dimer that, in turn, may coordinate the rearrangement of the transmembrane helices.

Talin-driven inside-out activation mechanism of platelet αIIbß3 integrin probed by multimicrosecond, all-atom molecular dynamics simulations.

Platelet aggregation is the consequence of the binding of extracellular bivalent ligands such as fibrinogen and von Willebrand factor to the high affinity, active state of integrin αIIbß3. This state is achieved through a so-called "inside-out" mechanism characterized by the membrane-assisted formation of a complex between the F2 and F3 subdomains of intracellular protein talin and the integrin ß3 tail. Here, we present the results of multi-microsecond, all-atom molecular dynamics simulations carried on the complete transmembrane (TM) and C-terminal (CT) domains of αIIbß3 integrin in an explicit lipid-water environment, and in the presence or absence of the talin-1 F2 and F3 subdomains. These large-scale simulations provide unprecedented molecular-level insights into the talin-driven inside-out activation of αIIbß3 integrin. Specifically, they suggest a preferred conformation of the complete αIIbß3 TM/CT domains in a lipid-water environment, and testable hypotheses of key intermolecular interactions between αIIbß3 integrin and the F2/F3 domains of talin-1. Notably, not only do these simulations give support to a stable left-handed reverse turn conformation of the αIIb juxtamembrane motif rather than a helical turn, but they raise the question as to whether TM helix separation is required for talin-driven integrin activation.

Bioactive conformations of two seminal delta opioid receptor penta-peptides inferred from free-energy profiles.

Delta-opioid (DOP) receptors are members of the G protein-coupled receptor (GPCR) sub-family of opioid receptors, and are evolutionarily related, with homology exceeding 70%, to cognate mu-opioid (MOP), kappa-opioid (KOP), and nociceptin opioid (NOP) receptors. DOP receptors are considered attractive drug targets for pain management because agonists at these receptors are reported to exhibit strong antinociceptive activity with relatively few side effects. Among the most potent analgesics targeting the DOP receptor are the linear and cyclic enkephalin analogs known as DADLE (Tyr-D-Ala-Gly-Phe-D-Leu) and DPDPE (Tyr-D-Pen-Gly-Phe-D-Pen), respectively. Several computational and experimental studies have been carried out over the years to characterize the conformational profile of these penta-peptides with the ultimate goal of designing potent peptidomimetic agonists for the DOP receptor. The computational studies published to date, however, have investigated only a limited range of timescales and used over-simplified representations of the solvent environment. We provide here a thorough exploration of the conformational space of DADLE and DPDPE in an explicit solvent, using microsecond-scale molecular dynamics and bias-exchange metadynamics simulations. Free-energy profiles derived from these simulations point to a small number of DADLE and DPDPE conformational minima in solution, which are separated by relatively small energy barriers. Candidate bioactive forms of these peptides are selected from identified common spatial arrangements of key pharmacophoric points within all sampled conformations.

Structural insights into the unexpected agonism of tetracyclic antidepressants at serotonin receptors 5-HT1eR and 5-HT1FR.

Serotonin [5-hydroxytryptamine (5-HT)] acts via 13 different receptors in humans. Of these receptor subtypes, all but 5-HT1eR have confirmed roles in native tissue and are validated drug targets. Despite 5-HT1eR's therapeutic potential and plausible druggability, the mechanisms of its activation remain elusive. To illuminate 5-HT1eR's pharmacology in relation to the highly homologous 5-HT1FR, we screened a library of aminergic receptor ligands at both receptors and observe 5-HT1eR/5-HT1FR agonism by multicyclic drugs described as pan-antagonists at 5-HT receptors. Potent agonism by tetracyclic antidepressants mianserin, setiptiline, and mirtazapine suggests a mechanism for their clinically observed antimigraine properties. Using cryo-EM and mutagenesis studies, we uncover and characterize unique agonist-like binding poses of mianserin and setiptiline at 5-HT1eR distinct from similar drug scaffolds in inactive-state 5-HTR structures. Together with computational studies, our data suggest that these binding poses alongside receptor-specific allosteric coupling in 5-HT1eR and 5-HT1FR contribute to the agonist activity of these antidepressants.