Multitarget ligands that comprise opioid/nonopioid pharmacophores for pain management: Current state of the science

Chronic pain, which affects more than one-third of the world's population, represents one of the greatest medical challenges of the 21st century, yet its effective management remains sub-optimal. The 'gold standard' for the treatment of moderate to severe pain consists of opioid ligands, such as morphine and fentanyl, that target the µ-opioid receptor (MOP). Paradoxically, these opioids also cause serious side effects, including constipation, respiratory depression, tolerance, and addiction. In addition, the development of opioid-use disorders, such as opioid diversion, misuse, and abuse, has led to the current opioid crisis, with dramatic increases in addiction, overdoses, and ultimately deaths. As pain is a complex, multidimensional experience involving a variety of pathways and mediators, dual or multitarget ligands that can bind to more than one receptor and exert complementary analgesic effects, represent a promising avenue for pain relief. Indeed, unlike monomodal therapeutic approaches, the modulation of several endogenous nociceptive systems can often result in an additive or even synergistic effect, thereby improving the analgesic-to-side-effect ratio. Here, we provide a comprehensive overview of research efforts towards the development of dual- or multi-targeting opioid/nonopioid hybrid ligands for effective and safer pain management. We reflect on the underpinning discovery rationale by discussing the design, medicinal chemistry, and in vivo pharmacological effects of multitarget antinociceptive compounds.

The World of GPCR dimers - Mapping dopamine receptor D2 homodimers in different activation states and configuration arrangements

G protein-coupled receptors (GPCRs) are known to dimerize, but the molecular and structural basis of GPCR dimers is not well understood. In this study, we developed a computational framework to generate models of symmetric and asymmetric GPCR dimers using different monomer activation states and identified their most likely interfaces with molecular details. We chose the dopamine receptor D2 (D2R) homodimer as a case study because of its biological relevance and the availability of structural information. Our results showed that transmembrane domains 4 and 5 (TM4 and TM5) are mostly found at the dimer interface of the D2R dimer and that these interfaces have a subset of key residues that are mostly nonpolar from TM4 and TM5, which was in line with experimental studies. In addition, TM2 and TM3 appear to be relevant for D2R dimers. In some cases, the inactive configuration is unaffected by the partnered protomer, whereas in others, the active protomer adopts the properties of an inactive receptor. Additionally, the β-arrestin configuration displayed the properties of an active receptor in the absence of an agonist, suggesting that a switch to another meta-state during dimerization occurred. Our findings are consistent with the experimental data, and this method can be adapted to study heterodimers and potentially extended to include additional proteins such as G proteins or β-arrestins. In summary, this approach provides insight into the impact of the conformational status of partnered protomers on the overall quaternary GPCR macromolecular structure and dynamics.

Key Residues in δ Opioid Receptor Allostery Explored by the Elastic Network Model and the Complex Network Model Combined with the Perturbation Method

Opioid receptors, a kind of G protein-coupled receptors (GPCRs), mainly mediate an analgesic response via allosterically transducing the signal of endogenous ligand binding in the extracellular domain to couple to effector proteins in the intracellular domain. The δ opioid receptor (DOP) is associated with emotional control besides pain control, which makes it an attractive therapeutic target. However, its allosteric mechanism and key residues responsible for the structural stability and signal communication are not completely clear. Here we utilize the Gaussian network model (GNM) and amino acid network (AAN) combined with perturbation methods to explore the issues. The constructed fcfGNM_MD, where the force constants are optimized with the inverse covariance estimation based on the correlated fluctuations from the available DOP molecular dynamics (MD) ensemble, shows a better performance than traditional GNM in reproducing residue fluctuations and cross-correlations and in capturing functionally low-frequency modes. Additionally, fcfGNM_MD can consider implicitly the environmental effects to some extent. The lowest mode can well divide DOP segments and identify the two sodium ion (important allosteric regulator) binding coordination shells, and from the fastest modes, the key residues important for structure stabilization are identified. Using fcfGNM_MD combined with a dynamic perturbation-response method, we explore the key residues related to the sodium ion binding. Interestingly, we identify not only the key residues in sodium ion binding shells but also the ones far away from the perturbation sites, which are involved in binding with DOP ligands, suggesting the possible long-range allosteric modulation of sodium binding for the ligand binding to DOP. Furthermore, utilizing the weighted AAN combined with attack perturbations, we identify the key residues for allosteric communication. This work helps strengthen the understanding of the allosteric communication mechanism in δ opioid receptor and can provide valuable information for drug design.

Biased Activation Mechanism Induced by GPCR Heterodimerization: Observations from μOR/δOR Dimers

GPCRs regulate multiple intracellular signaling cascades. Biasedly activating one signaling pathway over the others provides additional clinical utility to optimize GPCR-based therapies. GPCR heterodimers possess different functions from their monomeric states, including their selectivity to different transducers. However, the biased signaling mechanism induced by the heterodimerization remains unclear. Motivated by the issue, we select an important GPCR heterodimer (μOR/δOR heterodimer) as a case and use microsecond Gaussian accelerated molecular dynamics simulation coupled with potential of mean force and protein structure network (PSN) to probe mechanisms regarding the heterodimerization-induced constitutive β-arrestin activity and efficacy change of the agonist DAMGO. The results show that only the lowest energy state of the μOR/δOR heterodimer, which adopts a slightly outward shift of TM6 and an ICL2 conformation close to the receptor core, can selectively accommodate β-arrestins. PSN further reveals important roles of H8, ICL1, and ICL2 in regulating the constitutive β-arrestin-biased activity for the apo μOR/δOR heterodimer. In addition, the heterodimerization can allosterically alter the binding mode of DAMGO mainly by means of W7.35. Consequently, DAMGO transmits the structural signal mainly through TM6 and TM7 in the dimer, rather than TM3 similar to the μOR monomer, thus changing the efficacy of DAMGO from a balanced agonist to the β-arrestin-biased one. On the other side, the binding of DAMGO to the heterodimer can stabilize μOR/δOR heterodimers through a stronger interaction of TM1/TM1 and H8/H8, accordingly enhancing the interaction of μOR with δOR and the binding affinity of the dimer to the β-arrestin. The agonist DAMGO does not change main compositions of the regulation network from the dimer interface to the transducer binding pocket of the μOR protomer, but induces an increase in the structural communication of the network, which should contribute to the enhanced β-arrestin coupling. Our observations, for the first time, reveal the molecular mechanism of the biased signaling induced by the heterodimerization for GPCRs, which should be beneficial to more comprehensively understand the GPCR bias signaling.

Molecular Mechanisms of Diverse Activation Stimulated by Different Biased Agonists for the β2-Adrenergic Receptor

β2AR is an important drug target protein involving many diseases. Biased drugs induce specific signaling and provide additional clinical utility to optimize β2AR-based therapies. However, the biased signaling mechanism has not been elucidated. Motivated by the issue, we chose four agonists with divergent bias (balanced agonist, G-protein-biased agonist, and β-arrestin-biased agonists) and utilized Gaussian accelerated molecular dynamics simulation coupled with a dynamic network to probe the molecular mechanisms of distinct biased activation induced by the structural differences between the four agonists. Our simulations reveal that the G-protein-biased agonist induces an open conformation with the outward shifts of TM6 and TM7 for the intracellular domain, which will be beneficial to couple G protein. In contrast, the β-arrestin-biased agonists regulate an occluded conformation with a slightly outward movement of TM6 and an inward shift of TM7, which should favor β-arrestin signaling. The balanced agonist does not induce an observable outward shift for TM6 but, along with a slight tilt for TM7, leads to an inactive-like conformation. In addition, our results reveal the first time that ICL3 presents specific conformations with different agonists. The G-protein-biased agonist drives ICL3 to open so that the G protein-binding pocket can be available, while the β-arrestin-biased agonists induce ICL3 to form a closed conformation with a stable local α-helix. MM/PBSA analysis further reveals that the hydroxyl groups in the resorcinol of the G-protein-biased agonist form strong interactions with Y5.38 and S5.42, thus preventing tilting of the TM5 extracellular end. The catechol of the balanced agonist and the β-arrestin-biased ones induces the rearrangement of two hydrophobic residues F6.52 and W6.48. However, different from the balanced agonist, the ethyl substituent of β-arrestin-biased agonists forms additional hydrophobic interactions with W6.48 and F6.51 after the rearrangement, which should contribute to the β-arrestin bias. The shortest pathway analysis further reveals that the three residues Y7.43, N7.45, and N7.49 are crucial for allosterically regulating G-protein-biased signaling, while the two residues W6.48 and F6.44 make an important contribution to regulate β-arrestin-biased signaling. For the balanced agonist NE, the allosteric regulation pathway simultaneously involves the residue associated with G-protein-biased signaling like S5.46 and the residues related to β-arrestin-biased signaling like W6.48 and F6.44, thus producing unbiased signaling. The observations could advance our understanding of the biased activation mechanism on class A GPCRs and provide a useful guideline for the design of biased drugs.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Co-Evolution of Opioid and Adrenergic Ligands and Receptors: Shared, Complementary Modules Explain Evolution of Functional Interactions and Suggest Novel Engineering Possibilities

Cross-talk between opioid and adrenergic receptors is well-characterized and involves second messenger systems, the formation of receptor heterodimers, and the presence of extracellular allosteric binding regions for the complementary ligand; however, the evolutionary origins of these interactions have not been investigated. We propose that opioid and adrenergic ligands and receptors co-evolved from a common set of modular precursors so that they share binding functions. We demonstrate the plausibility of this hypothesis through a review of experimental evidence for molecularly complementary modules and report unexpected homologies between the two receptor types. Briefly, opioids form homodimers also bind adrenergic compounds; opioids bind to conserved extracellular regions of adrenergic receptors while adrenergic compounds bind to conserved extracellular regions of opioid receptors; opioid-like modules appear in both sets of receptors within key ligand-binding regions. Transmembrane regions associated with homodimerization of each class of receptors are also highly conserved across receptor types and implicated in heterodimerization. This conservation of multiple functional modules suggests opioid–adrenergic ligand and receptor co-evolution and provides mechanisms for explaining the evolution of their crosstalk. These modules also suggest the structure of a primordial receptor, providing clues for engineering receptor functions.

[MOPr-DOPr heteromer: the meaning and possibility as novel therapeutic target for pain control]

Many studies suggest opioid receptor (OPr) dimerization modulates the pharmacological properties of opiates. Specifically, heteromerization between OPr types has been reported to lead to changes in intracellular signaling. Thus, ligands targeting heteromers are expected to be novel therapeutic targets with reduced side effects. The heteromers of mu (MOPr) and delta (DOPr) are detected in brain regions involved in pain processing. The bivalent ligand or small molecule were identified as a MOPr-DOPr targeting ligand. These ligands exhibit antinociceptive properties similar to that of morphine with lesser antinociceptive tolerance as compared to morphine. Studies exploring the in vivo regulation of MOPr-DOPr heteromers, showed chronic morphine administration leads to an upregulation of these heteromers in select brain regions. Exploration of mechanisms underlying this phenomenon led us to the G protein-coupled receptor chaperone, RTP4, that is induced by chronic morphine and facilitates the heteromerization of MOPr and DOPr. In this review, I will introduce the simulated structure or property of MOPr-DOPr heteromer, its targeting ligands, and its intracellular regulatory mechanism that include a key molecule like RTP4 that could serve as a scaffold for the development of novel therapeutic drugs with reduced adverse effects, and hence may take place of the conventional clinical opioids.

Collective Dynamics of Ion Channels on Bilayer Lipid Membranes

Ion channels self-organize on cellular and organelle membranes as clusters and mutually modulate their gating behavior. It has been reported that the efficient information transfer is achieved by cooperative clustering of ion channels. To address the origin and nature of collective dynamics in ion channel clusters, a statistical mechanical model, namely, the Zimm-Bragg-type model in two dimensions with unequal weight distribution in channel-channel interactions, has been proposed. Nearest neighbor interaction along with next-nearest neighbor interaction has been considered, assuming symmetric spatial organization. The multichannel bilayer electrophysiology recordings of the voltage-dependent anion channel (VDAC) from rat brain mitochondria have been analyzed in order to test and further extend the model. The model successfully describes the multichannel gating behavior and self-organization of the VDAC cluster.

Ligand based conformational space studies of the μ-opioid receptor

BACKGROUND

G protein-coupled receptors (GPCRs) comprise a family of membrane proteins that can be activated by a variety of external factors. The μ-opioid receptor (MOR), a class A GPCR, is the main target of morphine. Recently, enhanced sampling molecular dynamics simulations of a constitutively active mutant of MOR in its apo form allowed us to capture the novel intermediate states of activation, as well as the active state. This prompted us to apply the same techniques to wild type MOR in complex with ligands, in order to explore their contributions to the receptor conformational changes in the activation process.

METHODS

MOR was modeled in complex with agonists (morphine, BU72), a partial agonist (naloxone benzoylhydrazone) and an antagonist (naloxone). Replica exchange with solute tempering (REST2) molecular dynamics simulations were carried out for all systems. Trajectory frames were clustered, and the activation state of each cluster was assessed by two different methods.

RESULTS

Cluster sizes and activation indices show that while agonists stabilized structures in a higher activation state, the antagonist behaved oppositely. Morphine tends to drive the receptor towards increasing R165-T279 distances, while naloxone tends to increase the NPxxYA motif conformational change.

CONCLUSIONS

Despite not observing a full transition between inactive and active states, an important conformational change of transmembrane helix 5 was observed and associated with a ligand-driven step of the process.

GENERAL SIGNIFICANCE

The activation process of GPCRs is widely studied but still not fully understood. Here we carried out a step forward in the direction of gaining more details of this process.

Endogenous Opiates and Behavior: 2018

This paper is the forty-first consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2018 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides and receptors as well as effects of opioid/opiate agonists and antagonists. The review is subdivided into the following specific topics: molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors (2), the roles of these opioid peptides and receptors in pain and analgesia in animals (3) and humans (4), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (5), opioid peptide and receptor involvement in tolerance and dependence (6), stress and social status (7), learning and memory (8), eating and drinking (9), drug abuse and alcohol (10), sexual activity and hormones, pregnancy, development and endocrinology (11), mental illness and mood (12), seizures and neurologic disorders (13), electrical-related activity and neurophysiology (14), general activity and locomotion (15), gastrointestinal, renal and hepatic functions (16), cardiovascular responses (17), respiration and thermoregulation (18), and immunological responses (19).

In Silico Analysis of a Highly Mutated Gene in Cancer Provides Insight into Abnormal mRNA Splicing: Splicing Factor 3B Subunit 1K700E Mutant

Cancer is the second leading cause of death worldwide. The etiology of the disease has remained elusive, but mutations causing aberrant RNA splicing have been considered one of the significant factors in various cancer types. The association of aberrant RNA splicing with drug/therapy resistance further increases the importance of these mutations. In this work, the impact of the splicing factor 3B subunit 1 (SF3B1) K700E mutation, a highly prevalent mutation in various cancer types, is investigated through molecular dynamics simulations. Based on our results, K700E mutation increases flexibility of the mutant SF3B1. Consequently, this mutation leads to i) disruption of interaction of pre-mRNA with SF3B1 and p14, thus preventing proper alignment of mRNA and causing usage of abnormal 3' splice site, and ii) disruption of communication in critical regions participating in interactions with other proteins in pre-mRNA splicing machinery. We anticipate that this study enhances our understanding of the mechanism of functional abnormalities associated with splicing machinery, thereby, increasing possibility for designing effective therapies to combat cancer at an earlier stage.

Binding Interactions of Ergotamine and Dihydroergotamine to 5-Hydroxytryptamine Receptor 1B (5-HT1b) Using Molecular Dynamics Simulations and Dynamic Network Analysis

Ergotamine (ERG) and dihydroergotamine (DHE), common migraine drugs, have small structural differences but lead to clinically important distinctions in their pharmacological profiles. For example, DHE is less potent than ERG by about 10-fold at the 5-hydroxytrptamine receptor 1B (5-HT_1B). Although the high-resolution crystal structures of the 5-HT_1B receptor with both ligands have been solved, the high similarity between these two complex structures does not sufficiently explain their activity differences and the activation mechanism of the receptor. Hence, an examination of the dynamic motion of both drugs with the receptor is required. In this study, we ran a total of 6.0 μs molecular dynamics simulations on each system. Our simulation data show the subtle variations between the two systems in terms of the ligand-receptor interactions and receptor secondary structures. More importantly, the ligand and protein root-mean-square fluctuations (RMSFs) for the two systems were distinct, with ERG having a trend of lower RMSF values, indicating it to be bound tighter to 5-HT_1B with less fluctuations. The molecular mechanism-general born surface area (MM-GBSA) binding energies illustrate this further, proving ERG has an overall stronger MM-GBSA binding energy. Analysis of several different microswitches has shown that the 5-HT_1B-ERG complex is in a more active conformation state than 5-HT_1B-DHE, which is further supported by the dynamic network model, with reference to mutagenesis data with the critical nodes and the first three low-energy modes from the normal mode analysis. We also identify Trp327^6.48 and Phe331^6.52 as key residues involved in the active state 5-HT_1B for both ligands. Using the detailed dynamic information from our analysis, we made predictions for possible modifications to DHE and ERG that yielded five derivatives that might have more favorable binding energies and reduced structural fluctuations.

Exploring the Activation Mechanism of a Metabotropic Glutamate Receptor Homodimer via Molecular Dynamics Simulation

Metabotropic glutamate receptors of class C GPCRs exist as constitutive dimers, which play important roles in activating excitatory synapses of the central nervous system. However, the activation mechanism induced by agonists has not been clarified in experiments. To address the problem, we used microsecond all-atom molecular dynamics (MD) simulation couple with protein structure network (PSN) to explore the glutamate-induced activation for the mGluR1 homodimer. The results indicate that glutamate binding stabilizes not only the closure of Venus flytrap domains but also the polar interaction of LB2-LB2, in turn keeping the extracelluar domain in the active state. The activation of the extracelluar domain drives transmembrane domains (TMDs) of the two protomers closer and induces asymmetric activation for the TMD domains of the two protomers. One protomer with lower binding affinity to the agonist is activated, while the other protomer with higher binding energy is still in the inactive state. The PSN analysis identifies the allosteric regulation pathway from the ligand-binding pocket in the extracellular domain to the G-protein binding site in the intracellular TMD region and further reveals that the asymmetric activation is attributed to a combination of trans-pathway and cis-pathway regulations from two glumatates, rather than a single activation pathway. These observations could provide valuable molecular information for understanding of the structure and the implications in drug efficacy for the class C GPCR dimers.

Prediction and targeting of GPCR oligomer interfaces

GPCR oligomerization has emerged as a hot topic in the GPCR field in the last years. Receptors that are part of these oligomers can influence each other's function, although it is not yet entirely understood how these interactions work. The existence of such a highly complex network of interactions between GPCRs generates the possibility of alternative targets for new therapeutic approaches. However, challenges still exist in the characterization of these complexes, especially at the interface level. Different experimental approaches, such as FRET or BRET, are usually combined to study GPCR oligomer interactions. Computational methods have been applied as a useful tool for retrieving information from GPCR sequences and the few X-ray-resolved oligomeric structures that are accessible, as well as for predicting new and trustworthy GPCR oligomeric interfaces. Machine-learning (ML) approaches have recently helped with some hindrances of other methods. By joining and evaluating multiple structure-, sequence- and co-evolution-based features on the same algorithm, it is possible to dilute the issues of particular structures and residues that arise from the experimental methodology into all-encompassing algorithms capable of accurately predict GPCR-GPCR interfaces. All these methods used as a single or a combined approach provide useful information about GPCR oligomerization and its role in GPCR function and dynamics. Altogether, we present experimental, computational and machine-learning methods used to study oligomers interfaces, as well as strategies that have been used to target these dynamic complexes.

Conformation Transition of Intracellular Part of Glucagon Receptor in Complex With Agonist Glucagon by Conventional and Accelerated Molecular Dynamics Simulations

The inactive conformations of glucagon receptor (GCGR) are widely reported by crystal structures that support the precision structure for drug discovery of type 2 diabetes. The previous study shows that the intracellular part is open in the glucagon-bound GCGR (glu-GCGR) and closed in the apo-GCGR by accelerated molecular dynamics (aMD) simulations. However, the crystal structure of GCGR in complex with partial agonist shows that the intracellular part is closed in the inactive conformation. To understand the differences between the studies of aMD simulations and crystal structure, the 2,500 ns conventional molecular dynamics (cMD) simulations are performed on the simulated model of glu-GCGR. The result shows that the transmembrane helices (TMH) 6 of glu-GCGR is outward ~4 Å to drive the intracellular part of glu-GCGR open until ~390 ns cMD simulations. The (TMH) 6 of glu-GCGR becomes closed after ~490 ns cMD simulations, which are consistent with the crystal structure of GCGR in complex with the partial agonist. To further elucidate the activation mechanism of GCGR deeply, the simulated models of glu-GCGR, apo-GCGR, and antagonist-bound GCGR (ant-GCGR) are constructed to perform 10 of parallel 300 ns aMD simulations, respectively. The results show that both of glu-GCGR and apo-GCGR can generate the open conformations of the intracellular part. But the glu-GCGR has the higher percentage of open conformations than apo-GCGR. The ant-GCGR is restricted to generate the open conformations of the intracellular part by antagonist MK-0893. It indicates that the glu-GCGR, apo-GCGR, and ant-GCGR can be distinguished by the aMD simulated method. Free energy landscape shows that the open conformations of the intracellular part of GCGR are in intermediate state. Our results show that aMD simulations enhance the space samplings of open conformations of GCGR via adding extra boost potential. It indicates that the aMD simulations are an effective way for drug discovery of GCGR.

Probing the Druggablility on the Interface of the Protein-Protein Interaction and Its Allosteric Regulation Mechanism on the Drug Screening for the CXCR4 Homodimer

Modulating protein–protein interactions (PPIs) with small drug-like molecules targeting it exhibits great promise in modern drug discovery. G protein-coupled receptors (GPCRs) are the largest family of targeted proteins and could form dimers in living biological cells through PPIs. However, compared to drug development of the orthosteric site, there has been lack of investigations on the druggability of the PPI interface for GPCRs and its functional implication on experiments. Thus, in order to address these issues, we constructed a novel computational strategy, which involved in molecular dynamics simulation, virtual screening and protein structure network (PSN), to study one representative GPCR homodimer (CXCR4). One druggable pocket was identified in the PPI interface and one small molecule targeting it was screened, which could strengthen PPI mainly through hydrophobic interaction between the benzene rings of the PPI molecule and TM4 of the receptor. The PSN results further reveals that the PPI molecule could increase the number of the allosteric regulation pathways between the druggable pocket of the dimer interface to the orthostatic site for the subunit A but only play minor role for the other subunit B, leading to the asymmetric change in the volume of the binding pockets for the two subunits (increase for the subunit A and minor change for the subunit B). Consequently, the screening performance of the subunit A to the antagonists is enhanced while the subunit B is unchanged nearly, implying that the PPI molecule may be beneficial to enhance the drug efficacies of the antagonists. In addition, one main regulation pathway with the highest frequency was identified for the subunit A, which consists of Trp195^5.34–Tyr190^ECL2–Val196^5.35–Gln200^5.39–Asp262^6.58–Cys28^N-term, revealing their importance in the allosteric regulation from the PPI molecule. The observations from the work could provide valuable information for the development of the PPI drug-like molecule for GPCRs.

The effect of dimerization on the activation and conformational dynamics of adenosine A1 receptor

The adenosine A1 receptor (A1R) is one of four adenosine receptors in humans, which are involved in the function of the cardiovascular, respiratory and central nervous systems. Experimental results indicate that A1R can form a homodimer and that the protomer-protomer interaction in the A1R dimer is related to certain pharmacological characteristics of A1R activation. In this work, we performed docking, metadynamics simulation, conventional molecular dynamics simulations, Gaussian-accelerated molecular dynamics simulations, potential of mean force calculations, dynamic cross-correlation motions analysis and community network analysis to study the binding mode of 5'-N-ethylcarboxamidoadenosine (NECA) to A1R and the effect of dimerization on the activation of A1R. Our results show that NECA binds to A1R in a similar mode to adenosine in the A1R crystal structure and NECA in the A2AR crystal structure. The A1R homodimer can be activated by one or two agonists with NECA occupying its orthosteric pockets in one (which we call the NECA-A1R system) or both protomers (which we call the dNECA-A1R system). In the NECA-A1R system, activation is predicated in the protomer without NECA bound. In the dNECA-A1R system, only one protomer achieves the active state. These findings suggest an asymmetrical activation mechanism of the homodimer and a negative cooperativity between the two protomers. We envision that our results may further facilitate the drug development of A1R.

Computational prediction of GPCR oligomerization

There has been a recent and prolific expansion in the number of GPCR crystal structures being solved: in both active and inactive forms and in complex with ligand, with G protein and with each other. Despite this, there is relatively little experimental information about the precise configuration of GPCR oligomers during these different biologically relevant states. While it may be possible to identify the experimental conditions necessary to crystallize a GPCR preferentially in a specific structural conformation, computational approaches afford a potentially more tractable means of describing the probability of formation of receptor dimers and higher order oligomers. Ensemble-based computational methods based on structurally determined dimers, coupled with a computational workflow that uses quantum mechanical methods to analyze the chemical nature of the molecular interactions at a GPCR dimer interface, will generate the reproducible and accurate predictions needed to predict previously unidentified GPCR dimers and to inform future advances in our ability to understand and begin to precisely manipulate GPCR oligomers in biological systems. It may also provide information needed to achieve an increase in the number of experimentally determined oligomeric GPCR structures.