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

Dynamical Reweighting for Biased Rare Event Simulations

Dynamical reweighting techniques aim to recover the correct molecular dynamics from a simulation at a modified potential energy surface. They are important for unbiasing enhanced sampling simulations of molecular rare events. Here, we review the theoretical frameworks of dynamical reweighting for modified potentials. Based on an overview of kinetic models with increasing level of detail, we discuss techniques to reweight two-state dynamics, multistate dynamics, and path integrals. We explore the natural link to transition path sampling and how the effect of nonequilibrium forces can be reweighted. We end by providing an outlook on how dynamical reweighting integrates with techniques for optimizing collective variables and with modern potential energy surfaces.

Characterization of binding kinetics and intracellular signaling of new psychoactive substances targeting cannabinoid receptor using transition-based reweighting method

New psychoactive substances (NPS) targeting cannabinoid receptor 1 pose a significant threat to society as recreational abusive drugs that have pronounced physiological side effects. These greater adverse effects compared to classical cannabinoids have been linked to the higher downstream β-arrestin signaling. Thus, understanding the mechanism of differential signaling will reveal important structure-activity relationship essential for identifying and potentially regulating NPS molecules. In this study, we simulate the slow (un)binding process of NPS MDMB-Fubinaca and classical cannabinoid HU-210 from CB1 using multi-ensemble simulation to decipher the effects of ligand binding dynamics on downstream signaling. The transition-based reweighing method is used for the estimation of transition rates and underlying thermodynamics of (un)binding processes of ligands with nanomolar affinities. Our analyses reveal major interaction differences with transmembrane TM7 between NPS and classical cannabinoids. A variational autoencoder-based approach, neural relational inference (NRI), is applied to assess the allosteric effects on intracellular regions attributable to variations in binding pocket interactions. NRI analysis indicate a heightened level of allosteric control of NPxxY motif for NPS-bound receptors, which contributes to the higher probability of formation of a crucial triad interaction (Y7.53-Y5.58-T3.46) necessary for stronger β-arrestin signaling. Hence, in this work, MD simulation, data-driven statistical methods, and deep learning point out the structural basis for the heightened physiological side effects associated with NPS, contributing to efforts aimed at mitigating their public health impact.

Stereoselective recognition of morphine enantiomers by -opioid receptor

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor (MOR) exhibits binding affinity towards (-)-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the (+)-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of (-)-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast, (+)-morphine fails to sustain the activation state of MOR. Furthermore, the results suggest that specific residues, namely D1142.50 and D1473.32, are deprotonated in the active state of MOR bound to (-)-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

IUPHAR themed review: Opioid efficacy, bias, and selectivity

Drugs acting at the opioid receptor family are clinically used to treat chronic and acute pain, though they represent the second line of treatment behind GABA analogs, antidepressants and SSRI's. Within the opioid family mu and kappa opioid receptor are commonly targeted. However, activation of the mu opioid receptor has side effects of constipation, tolerance, dependence, euphoria, and respiratory depression; activation of the kappa opioid receptor leads to dysphoria and sedation. The side effects of mu opioid receptor activation have led to mu receptor drugs being widely abused with great overdose risk. For these reasons, newer safer opioid analgesics are in high demand. For many years a focus within the opioid field was finding drugs that activated the G protein pathway at mu opioid receptor, without activating the β-arrestin pathway, known as biased agonism. Recent advances have shown that this may not be the way forward to develop safer analgesics at mu opioid receptor, though there is still some promise at the kappa opioid receptor. Here we discuss recent novel approaches to develop safer opioid drugs including efficacy vs bias and fine-tuning receptor activation by targeting sub-pockets in the orthosteric site, we explore recent works on the structural basis of bias, and we put forward the suggestion that Gα subtype selectivity may be an exciting new area of interest.

Activation/Deactivation Free-Energy Profiles for the β2-Adrenergic Receptor: Ligand Modes of Action

We use enhanced-sampling simulations with an effective collective variable to study the activation of the β2-adrenergic receptor in the presence of ligands with different efficacy. The free-energy profiles are computed for the ligand-free (apo) receptor and binary (apo-receptor + G-protein α-subunit and receptor + ligand) and ternary complexes. The results are not only compatible with available experiments but also allow unprecedented structural insight into the nature of GPCR conformations along the activation pathway and their role in the activation mechanism. In particular, the simulations reveal an unexpected mode of action of partial agonists such as salmeterol and salbutamol that arises already in the binary complex without the G-protein. Specific differences in the polar interactions with residues in TM5, which are required to stabilize an optimal TM6 conformation that facilitates G-protein binding and receptor activation, play a major role in differentiating them from full agonists.

Bringing GPCR Structural Biology to Medical Applications: Insights from Both V2 Vasopressin and Mu-Opioid Receptors

G-protein coupled receptors (GPCRs) are versatile signaling proteins that regulate key physiological processes in response to a wide variety of extracellular stimuli. The last decade has seen a revolution in the structural biology of clinically important GPCRs. Indeed, the improvement in molecular and biochemical methods to study GPCRs and their transducer complexes, together with advances in cryo-electron microscopy, NMR development, and progress in molecular dynamic simulations, have led to a better understanding of their regulation by ligands of different efficacy and bias. This has also renewed a great interest in GPCR drug discovery, such as finding biased ligands that can either promote or not promote specific regulations. In this review, we focus on two therapeutically relevant GPCR targets, the V2 vasopressin receptor (V2R) and the mu-opioid receptor (µOR), to shed light on the recent structural biology studies and show the impact of this integrative approach on the determination of new potential clinical effective compounds.

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.

Molecular Dynamics Simulations of Ion Permeation in Human Voltage-Gated Sodium Channels

The recent determination of cryo-EM structures of voltage-gated sodium (Na_v) channels has revealed many details of these proteins. However, knowledge of ionic permeation through the Na_v pore remains limited. In this work, we performed atomistic molecular dynamics (MD) simulations to study the structural features of various neuronal Na_v channels based on homology modeling of the cryo-EM structure of the human Na_v1.4 channel and, in addition, on the recently resolved configuration for Na_v1.2. In particular, single Na⁺ permeation events during standard MD runs suggest that the ion resides in the inner part of the Na_v selectivity filter (SF). On-the-fly free energy parametrization (OTFP) temperature-accelerated molecular dynamics (TAMD) was also used to calculate two-dimensional free energy surfaces (FESs) related to single/double Na⁺ translocation through the SF of the homology-based Na_v1.2 model and the cryo-EM Na_v1.2 structure, with different realizations of the DEKA filter domain. These additional simulations revealed distinct mechanisms for single and double Na⁺ permeation through the wild-type SF, which has a charged lysine in the DEKA ring. Moreover, the configurations of the ions in the SF corresponding to the metastable states of the FESs are specific for each SF motif. Overall, the description of these mechanisms gives us new insights into ion conduction in human Na_v cryo-EM-based and cryo-EM configurations that could advance understanding of these systems and how they differ from potassium and bacterial Na_v channels.

Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor

The United States is experiencing the most profound and devastating opioid crisis in history, with the number of deaths involving opioids, including prescription and illegal opioids, continuing to climb over the past two decades. This severe public health issue is difficult to combat as opioids remain a crucial treatment for pain, and at the same time, they are also highly addictive. Opioids act on the opioid receptor, which in turn activates its downstream signaling pathway that eventually leads to an analgesic effect. Among the four types of opioid receptors, the µ subtype is primarily responsible for the analgesic cascade. This review describes available 3D structures of the µ opioid receptor in the protein data bank and provides structural insights for the binding of agonists and antagonists to the receptor. Comparative analysis on the atomic details of the binding site in these structures was conducted and distinct binding interactions for agonists, partial agonists, and antagonists were observed. The findings in this article deepen our understanding of the ligand binding activity and shed some light on the development of novel opioid analgesics which may improve the risk benefit balance of existing opioids.

Sodium regulates PLC and IP3 R-mediated calcium signaling in invasive breast cancer cells

Intracellular Ca2+ signaling and Na+ homeostasis are inextricably linked via ion channels and co-transporters, with alterations in the concentration of one ion having profound effects on the other. Evidence indicates that intracellular Na+ concentration ([Na+ ]i ) is elevated in breast tumors, and that aberrant Ca2+ signaling regulates numerous key cancer hallmark processes. The present study therefore aimed to determine the effects of Na+ depletion on intracellular Ca2+ handling in metastatic breast cancer cell lines. The relationship between Na+ and Ca2+ was probed using fura-2 and SBFI fluorescence imaging and replacement of extracellular Na+ with equimolar N-methyl-D-glucamine (0Na+ /NMDG) or choline chloride (0Na+ /ChoCl). In triple-negative MDA-MB-231 and MDA-MB-468 cells and Her2+ SKBR3 cells, but not ER+ MCF-7 cells, 0Na+ /NMDG and 0Na+ /ChoCl resulted in a slow, sustained depletion in [Na+ ]i that was accompanied by a rapid and sustained increase in intracellular Ca2+ concentration ([Ca2+ ]i ). Application of La3+ in nominal Ca2+ -free conditions had no effect on this response, ruling out reverse-mode NCX activity and Ca2+ entry channels. Moreover, the Na+ -linked [Ca2+ ]i increase was independent of membrane potential hyperpolarization (NS-1619), but was inhibited by pharmacological blockade of IP3 receptors (2-APB), phospholipase C (PLC, U73122) or following depletion of endoplasmic reticulum Ca2+ stores (cyclopiazonic acid). Thus, Na+ is linked to PLC/IP3 -mediated activation of endoplasmic reticulum Ca2+ release in metastatic breast cancer cells and this may have an important role in breast tumors where [Na+ ]i is perturbed.

Structure-based design of bitopic ligands for the µ-opioid receptor

Mu-opioid receptor (µOR) agonists such as fentanyl have long been used for pain management, but are considered a major public health concern owing to their adverse side effects, including lethal overdose1. Here, in an effort to design safer therapeutic agents, we report an approach targeting a conserved sodium ion-binding site2 found in µOR3 and many other class A G-protein-coupled receptors with bitopic fentanyl derivatives that are functionalized via a linker with a positively charged guanidino group. Cryo-electron microscopy structures of the most potent bitopic ligands in complex with µOR highlight the key interactions between the guanidine of the ligands and the key Asp2.50 residue in the Na+ site. Two bitopics (C5 and C6 guano) maintain nanomolar potency and high efficacy at Gi subtypes and show strongly reduced arrestin recruitment-one (C6 guano) also shows the lowest Gz efficacy among the panel of µOR agonists, including partial and biased morphinan and fentanyl analogues. In mice, C6 guano displayed µOR-dependent antinociception with attenuated adverse effects, supporting the µOR sodium ion-binding site as a potential target for the design of safer analgesics. In general, our study suggests that bitopic ligands that engage the sodium ion-binding pocket in class A G-protein-coupled receptors can be designed to control their efficacy and functional selectivity profiles for Gi, Go and Gz subtypes and arrestins, thus modulating their in vivo pharmacology.

Modeling Ensembles of Enzyme Reaction Pathways with Hi-MSM Reveals the Importance of Accounting for Pathway Diversity

Conventional quantum mechanical-molecular mechanics (QM/MM) simulation approaches for modeling enzyme reactions often assume that there is one dominant reaction pathway and that this pathway can be sampled starting from an X-ray structure of the enzyme. These assumptions reduce computational cost; however, their validity has not been extensively tested. This is due in part to the lack of a rigorous formalism for integrating disparate pathway information from dynamical QM/MM calculations. Here, we present a way to model ensembles of reaction pathways efficiently using a divide-and-conquer strategy through Hierarchical Markov State Modeling (Hi-MSM). This approach allows information on multiple, distinct pathways to be incorporated into a chemical kinetic model, and it allows us to test these two assumptions. Applying Hi-MSM to the reaction carried out by dihydrofolate reductase (DHFR) we find (i) there are multiple, distinct pathways significantly contributing to the overall flux of the reaction that the conventional approach does not identify and (ii) that the conventional approach does not identify the dominant reaction pathway. Thus, both assumptions underpinning the conventional approach are violated. Since DHFR is a relatively small enzyme, and configuration space scales exponentially with protein size, accounting for multiple reaction pathways is likely to be necessary for most enzymes.

Translocation Mechanism of Allosteric Sodium Ions in β2-Adrenoceptor

The allosteric modulation of G-protein-coupled receptors (GPCRs) by sodium ions has received significant attention as the crystal structures of several receptors show the binding of sodium ions (Na⁺) at the conserved D^2.50. Theoretical studies have shown that extracellular Na⁺ would enter the allosteric D^2.50 via the orthosteric site. However, it remains unclear how the bound allosteric Na⁺ would leave the GPCRs. In this study, we performed molecular dynamics (MD) simulations to illustrate the energy barriers of Na⁺ transfer through the transmembrane helix bundle of β₂AR. In contrast to the postulations from other GPCRs, the translocation of this allosteric Na⁺ into the intracellular side is found to be significantly difficult. Hence, the translocation direction could be receptor-specific.

Estimation of binding rates and affinities from multiensemble Markov models and ligand decoupling

Accurate and efficient simulation of the thermodynamics and kinetics of protein-ligand interactions is crucial for computational drug discovery. Multiensemble Markov Model (MEMM) estimators can provide estimates of both binding rates and affinities from collections of short trajectories but have not been systematically explored for situations when a ligand is decoupled through scaling of non-bonded interactions. In this work, we compare the performance of two MEMM approaches for estimating ligand binding affinities and rates: (1) the transition-based reweighting analysis method (TRAM) and (2) a Maximum Caliber (MaxCal) based method. As a test system, we construct a small host-guest system where the ligand is a single uncharged Lennard-Jones (LJ) particle, and the receptor is an 11-particle icosahedral pocket made from the same atom type. To realistically mimic a protein-ligand binding system, the LJ ϵ parameter was tuned, and the system was placed in a periodic box with 860 TIP3P water molecules. A benchmark was performed using over 80 µs of unbiased simulation, and an 18-state Markov state model was used to estimate reference binding affinities and rates. We then tested the performance of TRAM and MaxCal when challenged with limited data. Both TRAM and MaxCal approaches perform better than conventional Markov state models, with TRAM showing better convergence and accuracy. We find that subsampling of trajectories to remove time correlation improves the accuracy of both TRAM and MaxCal and that in most cases, only a single biased ensemble to enhance sampled transitions is required to make accurate estimates.

Ionic Liquid@Metal-Organic Framework as a Solid Electrolyte in a Lithium-Ion Battery: Current Performance and Perspective at Molecular Level

Searching for a suitable electrolyte in a lithium-ion battery is a challenging task. The electrolyte must not only be chemically and mechanically stable, but also be able to transport lithium ions efficiently. Ionic liquid incorporated into a metal-organic framework (IL@MOF) has currently emerged as an interesting class of hybrid material that could offer excellent electrochemical properties. However, the understanding of the mechanism and factors that govern its fast ionic conduction is crucial as well. In this review, the characteristics and potential use of IL@MOF as an electrolyte in a lithium-ion battery are highlighted. The importance of computational methods is emphasized as a comprehensive tool to investigate the atomistic behavior of IL@MOF and its interaction in electrochemical environments.

Oncological drug discovery: AI meets structure-based computational research

The integration of machine learning and structure-based methods has proven valuable in the past as a way to prioritize targets and compounds in early drug discovery. In oncological research, these methods can be highly beneficial in addressing the diversity of neoplastic diseases portrayed by the different hallmarks of cancer. Here, we review six use case scenarios for integrated computational methods, namely driver prediction, computational mutagenesis, (off)-target prediction, binding site prediction, virtual screening, and allosteric modulation analysis. We address the heterogeneity of integration approaches and individual methods, while acknowledging their current limitations and highlighting their potential to bring drugs for personalized oncological therapies to the market faster.

Encoding mu-opioid receptor biased agonism with interaction fingerprints

Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein-ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling.

Universal Properties and Specificities of the β2-Adrenergic Receptor-Gs Protein Complex Activation Mechanism Revealed by All-Atom Molecular Dynamics Simulations

G protein-coupled receptors (GPCRs) are transmembrane proteins of high pharmacological relevance. It has been proposed that their activity is linked to structurally distinct, dynamically interconverting functional states and the process of activation relies on an interconnecting network of conformational switches in the transmembrane domain. However, it is yet to be uncovered how ligands with different extents of functional effect exert their actions. According to our recent hypothesis, based on indirect observations and the literature data, the transmission of the external stimulus to the intracellular surface is accompanied by the shift of macroscopic polarization in the transmembrane domain, furnished by concerted movements of highly conserved polar motifs and the rearrangement of polar species. In this follow-up study, we have examined the β2-adrenergic receptor (β2AR) to see if our hypothesis drawn from an extensive study of the μ-opioid receptor (MOP) is fundamental and directly transferable to other class A GPCRs. We have found that there are some general similarities between the two receptors, in agreement with previous studies, and there are some receptor-specific differences that could be associated with different signaling pathways.

Endogenous opiates and behavior: 2019

This paper is the forty-second consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2019 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 (1), the roles of these opioid peptides and receptors in pain and analgesia in animals (2) and humans (3), opioid-sensitive and opioid-insensitive effects of nonopioid analgesics (4), opioid peptide and receptor involvement in tolerance and dependence (5), stress and social status (6), learning and memory (7), eating and drinking (8), drug abuse and alcohol (9), sexual activity and hormones, pregnancy, development and endocrinology (10), mental illness and mood (11), seizures and neurologic disorders (12), electrical-related activity and neurophysiology (13), general activity and locomotion (14), gastrointestinal, renal and hepatic functions (15), cardiovascular responses (16), respiration and thermoregulation (17), and immunological responses (18).

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

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

Correlated Motions of Conserved Polar Motifs Lay out a Plausible Mechanism of G Protein-Coupled Receptor Activation

Recent advancements in the field of experimental structural biology have provided high-resolution structures of active and inactive state G protein-coupled receptors (GPCRs), a highly important pharmaceutical target family, but the process of transition between these states is poorly understood. According to the current theory, GPCRs exist in structurally distinct, dynamically interconverting functional states of which populations are shifted upon binding of ligands and intracellular signaling proteins. However, explanation of the activation mechanism, on an entirely structural basis, gets complicated when multiple activation pathways and active receptor states are considered. Our unbiased, atomistic molecular dynamics simulations of the μ opioid receptor (MOP) revealed that transmission of external stimulus to the intracellular surface of the receptor is accompanied by subtle, concerted movements of highly conserved polar amino acid side chains along the 7th transmembrane helix. This may entail the rearrangement of polar species and the shift of macroscopic polarization in the transmembrane domain, triggered by agonist binding. Based on our observations and numerous independent indications, we suggest amending the widely accepted theory that the initiation event of GPCR activation is the shift of macroscopic polarization between the ortho- and allosteric binding pockets and the intracellular G protein-binding interface.

Dissecting Role of Charged Residue from Transmembrane Domain 5 of Latent Membrane Protein 1 via In Silico Simulations and Wet-Lab Experiments

Charged residues are frequently found in the transmembrane segments of membrane proteins, which reside in the hydrophobic bilayer environment. Charged residues are critical for the function of membrane protein. However, studies of their role in protein oligomerization are limited. By taking the fifth transmembrane domain (TMD5) of latent membrane protein 1 from the Epstein-Barr virus as a prototype model, in silico simulations and wet-lab experiments were performed to investigate how the charged states affect transmembrane domain oligomerization. Molecular dynamics (MD) simulations showed that the D150-protonated TMD5 trimer was stable, whereas unprotonated D150 created bends in the helices which distort the trimeric structure. D150 was mutated to asparagine to mimic the protonated D150 in TMD5, and the MD simulations of different D150N TMD5 trimers supported that the protonation state of D150 was critical for the trimerization of TMD5. In silico mutations found that D150N TMD5 preferred to interact with TMD5 to form the heterotrimer (1 D150N TMD5:2 protonated TMD5s) rather than the heterotrimer (2 D150N TMD5s:1 protonated TMD5). D150R TMD5 interacted with TMD5 to form the heterotrimer (1 D150R TMD5:2 protonated TMD5). These in silico results imply that D150N TMD5 and D150R TMD5 peptides may be probes for disrupting TMD5 trimerization, which was supported by the dominant-negative ToxR assay in bacterial membranes. In all, this study elucidates the role of charged residues at the membrane milieu in membrane protein oligomerization and provides insight into the development of oligomerization-regulating peptides for modulating transmembrane domain lateral interactions.

Structural Mechanism of ω-Currents in a Mutated Kv7.2 Voltage Sensor Domain from Molecular Dynamics Simulations

Activation of voltage-gated ion channels is regulated by conformational changes of the voltage sensor domains (VSDs), four water- and ion-impermeable modules peripheral to the central, permeable pore domain. Anomalous currents, defined as ω-currents, have been recorded in response to mutations of residues on the VSD S4 helix and associated with ion fluxes through the VSDs. In humans, gene defects in the potassium channel Kv7.2 result in a broad range of epileptic disorders, from benign neonatal seizures to severe epileptic encephalopathies. Experimental evidence suggests that the R207Q mutation in S4, associated with peripheral nerve hyperexcitability, induces ω-currents at depolarized potentials, but the fine structural details are still elusive. In this work, we use atom-detailed molecular dynamics simulations and a refined model structure of the Kv7.2 VSD in the active conformation in a membrane/water environment to study the effect of R207Q and four additional mutations of proven clinical importance. Our results demonstrate that the R207Q mutant shows the most pronounced increase of hydration in the internal VSD cavity, a feature favoring the occurrence of ω-currents. Free energy and kinetics calculations of sodium permeation through the native and mutated VSD indicate as more favorable the formation of a cationic current in the latter. Overall, our simulations establish a mechanistic linkage between genetic variations and their physiological outcome, by providing a computational description that includes both thermodynamic and kinetic features of ion permeation associated with ω-currents.

Identification of ligand-specific G protein-coupled receptor states and prediction of downstream efficacy via data-driven modeling

Ligand binding stabilizes different G protein-coupled receptor states via a complex allosteric process that is not completely understood. Here, we have derived free energy landscapes describing activation of the β2 adrenergic receptor bound to ligands with different efficacy profiles using enhanced sampling molecular dynamics simulations. These reveal shifts toward active-like states at the Gprotein-binding site for receptors bound to partial and full agonists, and that the ligands modulate the conformational ensemble of the receptor by tuning protein microswitches. We indeed find an excellent correlation between the conformation of the microswitches close to the ligand binding site and in the transmembrane region and experimentally reported cyclic adenosine monophosphate signaling responses. Dimensionality reduction further reveals the similarity between the unique conformational states induced by different ligands, and examining the output of classifiers highlights two distant hotspots governing agonism on transmembrane helices 5 and 7.

Expansion of the "Sodium World" through Evolutionary Time and Taxonomic Space

In 1986, Vladimir Skulachev and his colleagues coined the term "Sodium World" for the group of diverse organisms with sodium (Na)-based bioenergetics. Albeit only few such organisms had been discovered by that time, the authors insightfully noted that "the great taxonomic variety of organisms employing the Na-cycle points to the ubiquitous distribution of this novel type of membrane-linked energy transductions". Here we used tools of bioinformatics to follow expansion of the Sodium World through the evolutionary time and taxonomic space. We searched for those membrane protein families in prokaryotic genomes that correlate with the use of the Na-potential for ATP synthesis by different organisms. In addition to the known Na-translocators, we found a plethora of uncharacterized protein families; most of them show no homology with studied proteins. In addition, we traced the presence of Na-based energetics in many novel archaeal and bacterial clades, which were recently identified by metagenomic techniques. The data obtained support the view that the Na-based energetics preceded the proton-dependent energetics in evolution and prevailed during the first two billion years of the Earth history before the oxygenation of atmosphere. Hence, the full capacity of Na-based energetics in prokaryotes remains largely unexplored. The Sodium World expanded owing to the acquisition of new functions by Na-translocating systems. Specifically, most classes of G-protein-coupled receptors (GPCRs), which are targeted by almost half of the known drugs, appear to evolve from the Na-translocating microbial rhodopsins. Thereby the GPCRs of class A, with 700 representatives in human genome, retained the Na-binding site in the center of the transmembrane heptahelical bundle together with the capacity of Na-translocation. Mathematical modeling showed that the class A GPCRs could use the energy of transmembrane Na-potential for increasing both their sensitivity and selectivity. Thus, GPCRs, the largest protein family coded by human genome, stem from the Sodium World, which encourages exploration of other Na-dependent enzymes of eukaryotes.

Exploring the activation pathway and Gi-coupling specificity of the μ-opioid receptor

Understanding the activation mechanism of the μ-opioid receptor (μ-OR) and its selective coupling to the inhibitory G protein (Gi) is vital for pharmaceutical research aimed at finding treatments for the opioid overdose crisis. Many attempts have been made to understand the mechanism of the μ-OR activation, following the elucidation of new crystal structures such as the antagonist- and agonist-bound μ-OR. However, the focus has not been placed on the underlying energetics and specificity of the activation process. An energy-based picture would not only help to explain this coupling but also help to explore why other possible options are not common. For example, one would like to understand why μ-OR is more selective to Gi than a stimulatory G protein (Gs). Our study used homology modeling and a coarse-grained model to generate all of the possible "end states" of the thermodynamic cycle of the activation of μ-OR. The end points were further used to generate reasonable intermediate structures of the receptor and the Gi to calculate two-dimensional free energy landscapes. The results of the landscape calculations helped to propose a plausible sequence of conformational changes in the μ-OR and Gi system and for exploring the path that leads to its activation. Furthermore, in silico alanine scanning calculations of the last 21 residues of the C terminals of Gi and Gs were performed to shed light on the selective binding of Gi to μ-OR. Overall, the present work appears to demonstrate the potential of multiscale modeling in exploring the action of G protein-coupled receptors.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

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

Opioid Pharmacology under the Microscope

The powerful analgesic effects of opioid drugs have captivated the interest of physicians and scientists for millennia, and the ability of opioid drugs to produce serious undesired effects has been recognized for a similar period of time (Kieffer and Evans, 2009). Many of these develop progressively with prolonged or repeated drug use and then persist, motivating particular interest in understanding how opioid drugs initiate adaptive or maladaptive modifications in neural function or regulation. Exciting advances have been made over the past several years in elucidating drug-induced changes at molecular, cellular, and physiologic scales of analysis. The present review will highlight some recent cellular studies that we believe bridge across scales and will focus on optical imaging approaches that put opioid drug action "under the microscope." SIGNIFICANCE STATEMENT: Opioid receptors are major pharmacological targets, but their signaling at the cellular level results from a complex interplay between pharmacology, regulation, subcellular localization, and membrane trafficking. This minireview discusses recent advances in understanding the cellular biology of opioid receptors, emphasizing particular topics discussed at the 50th anniversary of the International Narcotics Research Conference. Our goal is to highlight distinct signaling and regulatory properties emerging from the cellular biology of opioid receptors and discuss potential relevance to therapeutics.

A Computational Pipeline to Predict Cardiotoxicity: From the Atom to the Rhythm

RATIONALE

Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery.

OBJECTIVE

To predict the impact of a drug from the drug chemistry on the cardiac rhythm.

METHODS AND RESULTS

In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction.

CONCLUSIONS

We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

The fine art of preparing membrane transport proteins for biomolecular simulations: Concepts and practical considerations

Molecular dynamics (MD) simulations have developed into an invaluable tool in bimolecular research, due to the capability of the method in capturing molecular events and structural transitions that describe the function as well as the physiochemical properties of biomolecular systems. Due to the progressive development of more efficient algorithms, expansion of the available computational resources, as well as the emergence of more advanced methodologies, the scope of computational studies has increased vastly over time. We now have access to a multitude of online databases, software packages, larger molecular systems and novel ligands due to the phenomenon of emerging novel psychoactive substances (NPS). With so many advances in the field, it is understandable that novices will no doubt find it challenging setting up a protein-ligand system even before they run their first MD simulation. These initial steps, such as homology modelling, ligand docking, parameterization, protein preparation and membrane setup have become a fundamental part of the drug discovery pipeline, and many areas of biomolecular sciences benefit from the applications provided by these technologies. However, there still remains no standard on their usage. Therefore, our aim within this review is to provide a clear overview of a variety of concepts and methodologies to consider, providing a workflow for a case study of a membrane transport protein, the full-length human dopamine transporter (hDAT) in complex with different stimulants, where MD simulations have recently been applied successfully.

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

Agonist binding to G protein-coupled receptors (GPCRs) leads to conformational changes in the transmembrane region that activate cytosolic signaling pathways. Although high-resolution structures of different receptor states are available, atomistic details of allosteric signaling across the membrane remain elusive. We calculated free energy landscapes of β₂ adrenergic receptor activation using atomistic molecular dynamics simulations in an optimized string of swarms framework, which shed new light on how microswitches govern the equilibrium between conformational states. Contraction of the extracellular binding site in the presence of the agonist BI-167107 is obligatorily coupled to conformational changes in a connector motif located in the core of the transmembrane region. The connector is probabilistically coupled to the conformation of the intracellular region. An active connector promotes desolvation of a buried cavity, a twist of the conserved NPxxY motif, and an interaction between two conserved tyrosines in transmembrane helices 5 and 7 (Y–Y motif), which lead to a larger population of active-like states at the G protein binding site. This coupling is augmented by protonation of the strongly conserved Asp79^2.50. The agonist binding site hence communicates with the intracellular region via a cascade of locally connected microswitches. Characterization of these can be used to understand how ligands stabilize distinct receptor states and contribute to development drugs with specific signaling properties. The developed simulation protocol can likely be transferred to other class A GPCRs.

A Survey of Molecular Imaging of Opioid Receptors

The discovery of endogenous peptide ligands for morphine binding sites occurred in parallel with the identification of three subclasses of opioid receptor (OR), traditionally designated as μ, δ, and κ, along with the more recently defined opioid-receptor-like (ORL1) receptor. Early efforts in opioid receptor radiochemistry focused on the structure of the prototype agonist ligand, morphine, although N-[methyl-¹¹C]morphine, -codeine and -heroin did not show significant binding in vivo. [¹¹C]Diprenorphine ([¹¹C]DPN), an orvinol type, non-selective OR antagonist ligand, was among the first successful PET tracers for molecular brain imaging, but has been largely supplanted in research studies by the μ-preferring agonist [¹¹C]carfentanil ([¹¹C]Caf). These two tracers have the property of being displaceable by endogenous opioid peptides in living brain, thus potentially serving in a competition-binding model. Indeed, many clinical PET studies with [¹¹C]DPN or [¹¹C]Caf affirm the release of endogenous opioids in response to painful stimuli. Numerous other PET studies implicate μ-OR signaling in aspects of human personality and vulnerability to drug dependence, but there have been very few clinical PET studies of μORs in neurological disorders. Tracers based on naltrindole, a non-peptide antagonist of the δ-preferring endogenous opioid enkephalin, have been used in PET studies of δORs, and [¹¹C]GR103545 is validated for studies of κORs. Structures such as [¹¹C]NOP-1A show selective binding at ORL-1 receptors in living brain. However, there is scant documentation of δ-, κ-, or ORL1 receptors in healthy human brain or in neurological and psychiatric disorders; here, clinical PET research must catch up with recent progress in radiopharmaceutical chemistry.

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.

Harnessing Ion-Binding Sites for GPCR Pharmacology

Endogenous ions play important roles in the function and pharmacology of G-protein coupled receptors (GPCRs). Historically the evidence for ionic modulation of GPCR function dates to 1973 with studies of opioid receptors, where it was demonstrated that physiologic concentrations of sodium allosterically attenuated agonist binding. This Na+-selective effect was distinct from effects of other monovalent and divalent cations, with the latter usually counteracting sodium's negative allosteric modulation of binding. Since then, numerous studies documenting the effects of mono- and divalent ions on GPCR function have been published. While ions can act selectively and nonselectively at many sites in different receptors, the discovery of the conserved sodium ion site in class A GPCR structures in 2012 revealed the unique nature of Na+ site, which has emerged as a near-universal site for allosteric modulation of class A GPCR structure and function. In this review, we synthesize and highlight recent advances in the functional, biophysical, and structural characterization of ions bound to GPCRs. Taken together, these findings provide a molecular understanding of the unique roles of Na+ and other ions as GPCR allosteric modulators. We will also discuss how this knowledge can be applied to the redesign of receptors and ligand probes for desired functional and pharmacological profiles. SIGNIFICANCE STATEMENT: The function and pharmacology of GPCRs strongly depend on the presence of mono and divalent ions in experimental assays and in living organisms. Recent insights into the molecular mechanism of this ion-dependent allosterism from structural, biophysical, biochemical, and computational studies provide quantitative understandings of the pharmacological effects of drugs in vitro and in vivo and open new avenues for the rational design of chemical probes and drug candidates with improved properties.

Ligand-Dependent Sodium Ion Dynamics within the A2A Adenosine Receptor: A Molecular Dynamics Study

Sodium ions have long been known to reduce the binding of agonists in many class-A GPCRs while having little effect on antagonist binding. Here, using long-time scale classical all-atom molecular dynamics simulations, we explore, in atomic detail, the motion of sodium ions within the ligand-binding pocket of the A_2A adenosine receptor (A2A-AR) both in the presence and absence of ligands and in the active and inactive state. We identify novel secondary ion binding sites within the pocket and find that the types of ion motions within the pocket are highly dependent on the presence and type of ligand within the pocket. Our results provide a first step toward developing a molecular understanding of the impact of sodium ions on class-A GPCRs.

G protein-coupled receptors of class A harness the energy of membrane potential to increase their sensitivity and selectivity

The human genome contains about 700 genes of G protein-coupled receptors (GPCRs) of class A; these seven-helical membrane proteins are the targets of almost half of all known drugs. In the middle of the helix bundle, crystal structures reveal a highly conserved sodium-binding site, which is connected with the extracellular side by a water-filled tunnel. This binding site contains a sodium ion in those GPCRs that are crystallized in their inactive conformations but does not in those GPCRs that are trapped in agonist-bound active conformations. The escape route of the sodium ion upon the inactive-to-active transition and its very direction have until now remained obscure. Here, by modeling the available experimental data, we show that the sodium gradient over the cell membrane increases the sensitivity of GPCRs if their activation is thermodynamically coupled to the sodium ion translocation into the cytoplasm but decreases it if the sodium ion retreats into the extracellular space upon receptor activation. The model quantitatively describes the available data on both activation and suppression of distinct GPCRs by membrane voltage. The model also predicts selective amplification of the signal from (endogenous) agonists if only they, but not their (partial) analogs, induce sodium translocation. Comparative structure and sequence analyses of sodium-binding GPCRs indicate a key role for the conserved leucine residue in the second transmembrane helix (Leu2.46) in coupling sodium translocation to receptor activation. Hence, class A GPCRs appear to harness the energy of the transmembrane sodium potential to increase their sensitivity and selectivity.

Revisiting the Allosteric Regulation of Sodium Cation on the Binding of Adenosine at the Human A2A Adenosine Receptor: Insights from Supervised Molecular Dynamics (SuMD) Simulations

One of the most intriguing findings highlighted from G protein-coupled receptor (GPCR) crystallography is the presence, in many members of class A, of a partially hydrated sodium ion in the middle of the seven transmembrane helices (7TM) bundle. In particular, the human adenosine A2A receptor (A2A AR) is the first GPCR in which a monovalent sodium ion was crystallized in a distal site from the canonical orthosteric one, corroborating, from a structural point of view, its role as a negative allosteric modulator. However, the molecular mechanism by which the sodium ion influences the recognition of the A2A AR agonists is not yet fully understood. In this study, the supervised molecular dynamics (SuMD) technique was exploited to analyse the sodium ion recognition mechanism and how its presence influences the binding of the endogenous agonist adenosine. Due to a higher degree of flexibility of the receptor extracellular (EC) vestibule, we propose the sodium-bound A2A AR as less efficient in stabilizing the adenosine during the different steps of binding.

Utilization of Biased G Protein-Coupled ReceptorSignaling towards Development of Safer andPersonalized Therapeutics

G protein-coupled receptors (GPCRs) are involved in a wide variety of physiological processes. Therefore, approximately 40% of currently prescribed drugs have targeted this receptor family. Discovery of β-arrestin mediated signaling and also separability of G protein and β-arrestin signaling pathways have switched the research focus in the GPCR field towards development of biased ligands, which provide engagement of the receptor with a certain effector, thus enriching a specific signaling pathway. In this review, we summarize possible factors that impact signaling profiles of GPCRs such as oligomerization, drug treatment, disease conditions, genetic background, etc. along with relevant molecules that can be used to modulate signaling properties of GPCRs such as allosteric or bitopic ligands, ions, aptamers and pepducins. Moreover, we also discuss the importance of inclusion of pharmacogenomics and molecular dynamics simulations to achieve a holistic understanding of the relation between genetic background and structure and function of GPCRs and GPCR-related proteins. Consequently, specific downstream signaling pathways can be enriched while those that bring unwanted side effects can be prevented on a patient-specific basis. This will improve studies that centered on development of safer and personalized therapeutics, thus alleviating the burden on economy and public health.

Allostery in G protein-coupled receptors investigated by molecular dynamics simulations

G-protein-coupled receptors (GPCRs) are allosteric signaling machines that trigger distinct functional responses depending on the particular conformational state they adopt upon binding. This so-called GPCR functional selectivity is prompted by ligands of different efficacy binding at orthosteric or allosteric sites on the receptor, as well as by interactions with intracellular protein partners or other receptor types. Molecular dynamics (MD) simulations can provide important mechanistic, thermodynamic, and kinetic insights into these interactions at a level of molecular detail that is necessary to rightly inform modern drug discovery. Here, we review the most recent MD contributions to understanding GPCR allostery, with an emphasis on their strengths and limitations.