Molecular switches of the κ opioid receptor triggered by 6'-GNTI and 5'-GNTI

Opioid ligands addressing unconventional binding sites and more than one opioid receptor subtype

Opioid receptors (ORs) represent one of the most significant groups of G-protein coupled receptor (GPCR) drug targets and also act as prototypical models for GPCR function. In a constant effort to develop drugs with less side effects, and tools to explore the ORs nature and function, various (poly)pharmacological ligand design approaches have been performed. That is, besides classical ligands, a great number of bivalent ligands (i.e. aiming on two distinct OR subtypes), univalent heteromer-selective ligands and bitopic and allosteric ligands have been synthesized for the ORs. The scope of our review is to present the most important of the aforementioned ligands, highlight their properties and exhibit the current state-of-the-art pallet of promising drug candidates or useful molecular tools for the ORs.

Computational Methods for Understanding the Selectivity and Signal Transduction Mechanism of Aminomethyl Tetrahydronaphthalene to Opioid Receptors

Opioid receptors are members of the group of G protein-couple receptors, which have been proven to be effective targets for treating severe pain. The interactions between the opioid receptors and corresponding ligands and the receptor’s activation by different agonists have been among the most important fields in opioid research. In this study, with compound M1, an active metabolite of tramadol, as the clue compound, several aminomethyl tetrahydronaphthalenes were designed, synthesized and assayed upon opioid receptors. With the resultant compounds FW-AII-OH-1 (Ki = 141.2 nM for the κ opioid receptor), FW-AII-OH-2 (Ki = 4.64 nM for the δ opioid receptor), FW-DI-OH-2 (Ki = 8.65 nM for the δ opioid receptor) and FW-DIII-OH-2 (Ki = 228.45 nM for the δ opioid receptor) as probe molecules, the structural determinants responsible for the subtype selectivity and activation mechanisms were further investigated by molecular modeling and molecular dynamics simulations. It was shown that Y^7.43 was a key residue in determining the selectivity of the three opioid receptors, and W^6.58 was essential for the selectivity of the δ opioid receptor. A detailed stepwise discovered agonist-induced signal transduction mechanism of three opioid receptors by aminomethyl tetrahydronaphthalene compounds was proposed: the 3–7 lock between TM3 and TM7, the DRG lock between TM3 and TM6 and rearrangement of I^3.40, P^5.50 and F^6.44, which resulted in the cooperative movement in 7 TMs. Then, the structural relaxation left room for the binding of the G protein at the intracellular site, and finally the opioid receptors were activated.

Deciphering the molecular basis of the kappa opioid receptor selectivity: A Molecular Dynamics study

Selective antagonists for the kappa opioid receptor (KOP) have the potential to treat opiate and alcohol addiction, as well as depression and other CNS disorders. Over the years, the development of KOP-selective antagonists yielded very few successful compounds. Recently, N-substituted trans-3,4-dimethyl-4-(3-hydroxyphenyl)piperidines have emerged as a novel class of pure opioid receptor antagonists, including the marketed Mu opioid receptor (MOP) peripheral antagonist Alvimopan and the potent KOP antagonist JDTic. However, the selectivity determinants of this class of compounds towards the opioid receptor subtypes are still vague and understudied. In this work, we have performed Molecular Dynamics (MD) simulation to gain insights into the differential binding of this class of compounds into KOP, as exemplified by Alvimopan and JDTic. Our study indicated that the selectivity largely depends on ligands interaction with the selectivity pocket formed by Val108, Thr111, and Val118, supported by two additional polar and hydrophobic contacts with Asp138 and Trp287, respectively. Our results also demonstrate, for the first time, that non-morphinan ligands can still adopt the "message-address model" for KOP efficacy and selectivity by binding to Glu297.

Structural Characterization of KOR Inactive and Active States for 3D Pharmacology and Drug Discovery

The structure of the human kappa opioid receptor (KOR) in complex with the long-acting antagonist JDTic was solved crystallographically in 2012 and, along with structures of other opioid receptors, revolutionized our understanding of opioid system function and pharmacology. More recently, active state KOR structure was also determined, giving important insights into activation mechanisms of the receptor. In this review, we will discuss how the understanding of atomistic structures of KOR established a key platform for deciphering details of subtype and functional selectivity of KOR-targeting ligands and for discovery of new chemical probes with potentially beneficial pharmacological profiles.

Bias-inducing allosteric binding site in mu-opioid receptor signaling

Abstract

G-protein-biased agonism of the mu-opioid receptor (μ-OR) is emerging as a promising strategy in analgesia. A deep understanding of how biased agonists modulate and differentiate G-protein-coupled receptors (GPCR) signaling pathways and how this is transferred into the cell are open questions. Here, using extensive all-atom molecular dynamics simulations, we analyzed the binding recognition process and signaling effects of three prototype μ-OR agonists. Our suggested structural mechanism of biased signaling in μ-OR involves an allosteric sodium ion site, water networks, conformational rearrangements in conserved motifs and collective motions of loops and transmembrane helices. These analyses led us to highlight the relevance of a bias-inducing allosteric binding site in the understanding of μ-OR’s G-protein-biased signaling. These results also suggest a competitive equilibrium between the agonists and the allosteric sodium ion, where the bias-inducing allosteric binding site can be modulated by this ion or an agonist such as herkinorin. Notably, herkinorin arises as the archetype modulator of μ-OR and its interactive pattern could be used for screening efforts via protein–ligand interaction fingerprint (PLIF) studies.

Article highlights

Structural and Functional Characterization of Allatostatin Receptor Type-C of Thaumetopoea pityocampa, a Potential Target for Next-Generation Pest Control Agents

Insect neuropeptide receptors, including allatostatin receptor type C (AstR-C), a G protein-coupled receptor, are among the potential targets for designing next-generation pesticides that despite their importance in offering a new mode-of-action have been overlooked. Focusing on AstR-C of Thaumetopoea pityocampa, a common pest in Mediterranean countries, by employing resonance energy transfer-based methods, we showed Gαi/o coupling and β-arrestin recruitment of the receptor at sub-nanomolar and nanomolar ranges of the endogenous ligand, AST-C, respectively. Molecular docking and molecular dynamics simulation studies revealed the importance of extracellular loop 2 in AstRC/AST-C interaction, and a combination of in silico and in vitro approaches showed the substantial role of Q271^6.55 in G protein-dependent activation of AstR-C possibly via contributing to the flexibility of the receptor's structure. The functional and structural insights obtained on T. pit AstR-C positively assist future efforts in developing environmentally friendly pest control agents that are needed urgently.

The Use of Computational Approaches in the Discovery and Mechanism Study of Opioid Analgesics

Opioid receptors that belong to class A G protein-coupled receptors (GPCRs) are vital in pain control. In the past few years, published high-resolution crystal structures of opioid receptor laid a solid basis for both experimental and computational studies. Computer-aided drug design (CADD) has been established as a powerful tool for discovering novel lead compounds and for understanding activation mechanism of target receptors. Herein, we reviewed the computational-guided studies on opioid receptors for the discovery of new analgesics, the structural basis of receptor subtype selectivity, agonist interaction mechanism, and biased signaling mechanism.

Endogenous opiates and behavior: 2017

This paper is the fortieth consecutive installment of the annual anthological review of research concerning the endogenous opioid system, summarizing articles published during 2017 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).

Dynamical important residue network (DIRN): network inference via conformational change

MOTIVATION

Protein residue interaction network has emerged as a useful strategy to understand the complex relationship between protein structures and functions and how functions are regulated. In a residue interaction network, every residue is used to define a network node, adding noises in network post-analysis and increasing computational burden. In addition, dynamical information is often necessary in deciphering biological functions.

RESULTS

We developed a robust and efficient protein residue interaction network method, termed dynamical important residue network, by combining both structural and dynamical information. A major departure from previous approaches is our attempt to identify important residues most important for functional regulation before a network is constructed, leading to a much simpler network with the important residues as its nodes. The important residues are identified by monitoring structural data from ensemble molecular dynamics simulations of proteins in different functional states. Our tests show that the new method performs well with overall higher sensitivity than existing approaches in identifying important residues and interactions in tested proteins, so it can be used in studies of protein functions to provide useful hypotheses in identifying key residues and interactions.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Insights From Molecular Dynamics Simulations of a Number of G-Protein Coupled Receptor Targets for the Treatment of Pain and Opioid Use Disorders

Effective treatments for pain management remain elusive due to the dangerous side-effects of current gold-standard opioid analgesics, including the respiratory depression that has led to skyrocketing death rates from opioid overdoses over the past decade. In an attempt to address the horrific opioid crisis worldwide, the National Institute on Drug Abuse has recently proposed boosting research on specific pharmacological mechanisms mediated by a number of G protein-coupled receptors (GPCRs). This research is expected to expedite the discovery of medications for opioid overdose and opioid use disorders, leading toward a safer and more effective treatment of pain. Here, we review mechanistic insights from recent all-atom molecular dynamics simulations of a specific subset of GPCRs for which high-resolution experimental structures are available, including opioid, cannabinoid, orexin, metabotropic glutamate, and dopamine receptor subtypes.

Endogenous Opiates and Behavior: 2016

This paper is the thirty-ninth consecutive installment of the annual review of research concerning the endogenous opioid system. It summarizes papers published during 2016 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior, and the roles of these opioid peptides and receptors in pain and analgesia, stress and social status, tolerance and dependence, learning and memory, eating and drinking, drug abuse and alcohol, sexual activity and hormones, pregnancy, development and endocrinology, mental illness and mood, seizures and neurologic disorders, electrical-related activity and neurophysiology, general activity and locomotion, gastrointestinal, renal and hepatic functions, cardiovascular responses, respiration and thermoregulation, and immunological responses.

Computational insights into the G-protein-biased activation and inactivation mechanisms of the μ opioid receptor

The μ opioid receptor (OR), a member of the class A subfamily of G-protein coupled receptors (GPCRs), is a major target for the treatment of pain. G-protein biased μ-OR agonists promise to be developed as analgesics. Thus, TRV130, the first representative μ-OR ligand with G-protein bias, has entered into phase III clinical trials. To identify the detailed G-protein-biased activation and inactivation mechanisms of the μ-OR, we constructed five μ-OR systems that were in complexes with the G-protein-biased agonists TRV130 and BU72, the antagonists β-FNA and naltrexone, as well as the free receptor. We performed a series of conventional molecular dynamics simulations and analyses of G-protein-biased activation and inactivation mechanisms of μ-OR. Our results, together with previously reported mutation results, revealed the operating mode of the activation switch composed of residues W^6.48 and Y^7.43 (Ballesteros/Weinstein numbering), the activity of which was responsible for down- and up-regulation, respectively, of the β-arrestin signaling, which in turn affected G-protein-biased activation of μ-OR. TRV130 was found to stabilize W^6.48 by interacting with Y^7.43. In addition, we obtained useful information regarding μ-OR-biased activation, such as strong stabilization of W^7.35 through a hydrophobic ring interaction in the TRV130 system. These findings may facilitate understanding of μ-OR biased activation and the design of new biased ligands for GPCRs.

Allosteric inhibitor remotely modulates the conformation of the orthestric pockets in mutant IDH2/R140Q

Neomorphic mutation R140Q in the metabolic enzyme isocitrate dehydrogenase 2 (IDH2) is found to be a driver mutation in cancers. Recent studies revealed that allosteric inhibitors could selectively inhibit IDH2/R140Q and induce differentiation of TF-1 erythroleukemia and primary human AML cells. However, the allosteric inhibition mechanism is not very clear. Here, we report the results from computational studies that AGI-6780 binds tightly with the divalent cation binding helices at the homodimer interface and prevents the transition of IDH2/R140Q homodimer to a closed conformation that is required for catalysis, resulting in the decrease of the binding free energy of NADPHs. If the allosteric inhibitor is removed, the original open catalytic center of IDH2/R140Q will gradually reorganize to a quasi-closed conformation and the enzymatic activity might recover. Unlike IDH2/R140Q, AGI-6780 locks one monomer of the wild-type IDH2 in an inactive open conformation and the other in a half-closed conformation, which can be used to explain the selectivity of AGI-6780. Our results suggest that conformational changes are the primary contributors to the inhibitory potency of the allosteric inhibitor. Our study will also facilitate the understanding of the inhibitory and selective mechanisms of AG-221 (a promising allosteric inhibitor that has been approved by FDA) for mutant IDH2.

Insights into the function of opioid receptors from molecular dynamics simulations of available crystal structures

The opioid receptors are key targets in the treatment of acute and chronic pain, and the development of novel analgesics with reduced side effects is crucial in the search for more effective medications. The crystal structures of opioid receptors have provided a wealth of knowledge on many aspects of opioid receptor pharmacology and function, including ligand binding poses, location of the sodium allosteric binding site, conformational changes associated with activation and putative dimeric interfaces. These crystal structures also offer a starting point for molecular dynamics (MD) simulations to capture one aspect of drug design that static structures cannot resolve, namely protein dynamics. With the increase in computing power, MD simulations of crystal structures have become an influential tool in understanding the function of GPCRs in general. Here, we discuss lessons learned from MD simulations of opioid receptor crystal structures with reference to (i) the binding pathway of sodium to its crystallographic allosteric site, (ii) the dynamics of ligand-receptor and receptor-receptor interactions, both at the ligand- and G protein-binding sites, (iii) the binding pathway and binding pose of novel ligands, and (iv) opioid receptor oligomerization.

LINKED ARTICLES

This article is part of a themed section on Emerging Areas of Opioid Pharmacology. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.14/issuetoc.

Allosteric modulation model of the mu opioid receptor by herkinorin, a potent not alkaloidal agonist

Modulation of opioid receptors is the primary choice for pain management and structural information studies have gained new horizons with the recently available X-ray crystal structures. Herkinorin is one of the most remarkable salvinorin A derivative with high affinity for the mu opioid receptor, moderate selectivity and lack of nitrogen atoms on its structure. Surprisingly, binding models for herkinorin are lacking. In this work, we explore binding models of herkinorin using automated docking, molecular dynamics simulations, free energy calculations and available experimental information. Our herkinorin D-ICM-1 binding model predicted a binding free energy of -11.52 ± 1.14 kcal mol^-1 by alchemical free energy estimations, which is close to the experimental values -10.91 ± 0.2 and -10.80 ± 0.05 kcal mol^-1 and is in agreement with experimental structural information. Specifically, D-ICM-1 molecular dynamics simulations showed a water-mediated interaction between D-ICM-1 and the amino acid H297^6.52, this interaction coincides with the co-crystallized ligands. Another relevant interaction, with N127^2.63, allowed to rationalize herkinorin's selectivity to mu over delta opioid receptors. Our suggested binding model for herkinorin is in agreement with this and additional experimental data. The most remarkable observation derived from our D-ICM-1 model is that herkinorin reaches an allosteric sodium ion binding site near N150^3.35. Key interactions in that region appear relevant for the lack of β-arrestin recruitment by herkinorin. This interaction is key for downstream signaling pathways involved in the development of side effects, such as tolerance. Future SAR studies and medicinal chemistry efforts will benefit from the structural information presented in this work.

Toward Understanding the Structural Basis of Partial Agonism at the Dopamine D3 Receptor

Both dopamine D₃ receptor (D₃R) partial agonists and antagonists have been implicated as potential medications for substance use disorders. In contrast to antagonists, partial agonists may cause fewer side effects since they maintain some dopaminergic tone and may be less disruptive to normal neuronal functions. Here, we report three sets of 4-phenylpiperazine stereoisomers that differ considerably in efficacy: the (R)-enantiomers are antagonists/weak partial agonists, whereas the (S)-enantiomers are much more efficacious. To investigate the structural basis of partial agonism, we performed comparative microsecond-scale molecular dynamics simulations starting from the inactive state of D₃R in complex with these enantiomers. Analysis of the simulation results reveals common structural rearrangements near the ligand binding site induced by the bound (S)-enantiomers, but not by the (R)-enantiomers, that are features of partially activated receptor conformations. These receptor models bound with partial agonists may be useful for structure-based design of compounds with tailored efficacy profiles.