Predicted structures and dynamics for agonists and antagonists bound to serotonin 5-HT2B and 5-HT2C receptors

Molecular and structural insights into the 5-HT2C receptor as a therapeutic target for substance use disorders

Substance use disorder (SUD) is a chronic condition, with maintained abuse of a substance leading to physiological and psychological alterations and often changes in cognitive and social behaviours. Current therapies include psychotherapy coupled with medication; however, high relapse rates reveal the shortcomings of these therapies. The signalling, expression profile, and neurological function of the serotonin 2C receptor (5-HT2C receptor) make it a candidate of interest for the treatment of SUD. Recently, psychedelics, which broadly act at 5-HT2 receptors, have indicated potential for the treatment of SUD, implicating the 5-HT2C receptor. The modern psychedelic movement has rekindled interest in the 5-HT2C receptor, resulting in many new studies, especially structural analyses. This review explores the structural, molecular and cellular mechanisms governing 5-HT2C receptor function in the context of SUD. This provides the basis of the preclinical and clinical evidence for their role in SUD and highlights the potential for future exploration.

Development of Pharmacophore Models for the Important Off-Target 5-HT2B Receptor

Toxicity is a major cause of attrition in the development of pharmaceuticals, and the off-target effects are a frequent contributor. The 5-HT_2B receptor agonism is known to be responsible for a variety of safety concerns including valvular heart disease which was the cause for the withdrawal of several compounds from the market. An early detection of potential binding to this receptor is thus desirable. Herein, we present the identification of key amino acid residues in the active site of 5-HT_2B by molecular dynamics simulations, the development of pharmacophore models and their performance on in-house data, and a structurally highly diverse subset of Enamine REAL labeled for 5-HT_2B activity by a machine learning model. These models may be used as filters employed on screening compound sets for the early filtration of compounds with potential 5-HT_2B off-target liabilities.

"Selective" serotonin 5-HT2A receptor antagonists

Blockade of the serotonin 5-HT_2A G protein-coupled receptor (5-HT_2AR) is a fundamental pharmacological characteristic of numerous antipsychotic medications, which are FDA-approved to treat schizophrenia, bipolar disorder, and as adjunctive therapies in major depressive disorder. Meanwhile, activation of the 5-HT_2AR by serotonergic psychedelics may be useful in treating neuropsychiatric indications, including major depressive and substance use disorders. Serotonergic psychedelics and other 5-HT_2AR agonists, however, often bind other receptors, and standard 5-HT_2AR antagonists lack sufficient selectivity to make well-founded mechanistic conclusions about the 5-HT_2AR-dependent effects of these compounds and the general neurobiological function of 5-HT_2ARs. This review discusses the limitations and strengths of currently available "selective" 5-HT_2AR antagonists, the molecular determinants of antagonist selectivity at 5-HT_2ARs, and the utility of molecular pharmacological and computational methods in guiding the discovery of novel unambiguously selective 5-HT_2AR antagonists.

Ursolic acid enhances stress resistance, reduces ROS accumulation and prolongs life span in C. elegans serotonin-deficient mutants

INTRODUCTION

Depression and anxiety disorders contribute to the global disease burden. Ursolic acid (UA), a natural compound present in many vegetables, fruits and medicinal plants, was tested in vivo for its effect on (1) enhancing resistance to stress and (2) its effect on life span.

METHODS

The compound was tested for its antioxidant activity in C. elegans. Stress resistance was tested in the heat and osmotic stress assay. Additionally, the influence on normal life span was examined. RT-PCR was used to assess possible serotonin targets.

RESULTS

UA prolonged the life span of C. elegans. Additionally, UA significantly lowered reactive oxygen species (ROS). Molecular docking studies, PCR analysis and microscale thermophoresis (MST) supported the results that UA acts through serotonin receptors to enhance stress resistance.

DISCUSSION

Considering the urgent need for new and safe medications in the treatment of depression and anxiety disorders, our results indicate that UA may be a promising new drug candidate.

The 3D Structure of Human DP Prostaglandin G-Protein-Coupled Receptor Bound to Cyclopentanoindole Antagonist, Predicted Using the DuplexBiHelix Modification of the GEnSeMBLE Method

Prostaglandins play a critical physiological role in both cardiovascular and immune systems, acting through their interactions with 9 prostanoid G protein-coupled receptors (GPCRs). These receptors are important therapeutic targets for a variety of diseases including arthritis, allergies, type 2 diabetes, and cancer. The DP prostaglandin receptor is of interest because it has unique structural and physiological properties. Most notably, DP does not have the 3-6 ionic lock common to Class A GPCRs. However, the lack of X-ray structures for any of the 9 prostaglandin GPCRs hampers the application of structure-based drug design methods to develop more selective and active medications to specific receptors. We predict here 3D structures for the DP prostaglandin GPCR, based on the GEnSeMBLE complete sampling with hierarchical scoring (CS-HS) methodology. This involves evaluating the energy of 13 trillion packings to finally select the best 20 that are stable enough to be relevant for binding to antagonists, agonists, and modulators. To validate the predicted structures, we predict the binding site for the Merck cyclopentanoindole (CPI) selective antagonist docked to DP. We find that the CPI binds vertically in the 1-2-7 binding pocket, interacting favorably with residues R310^7.40 and K76^2.54 with additional interactions with S313^7.43, S316^7.46, S19^1.35, etc. This binding site differs significantly from that of antagonists to known Class A GPCRs where the ligand binds in the 3-4-5-6 region. We find that the predicted binding site leads to reasonable agreement with experimental Structure-Activity Relationship (SAR). We suggest additional mutation experiments including K76^2.54, E129^3.49, L123^3.43, M270^6.40, F274^6.44 to further validate the structure, function, and activation mechanism of receptors in the prostaglandin family. Our structures and binding sites are largely consistent and improve upon the predictions by Li et al. ( J. Am. Chem. Soc. 2007 , 129 ( 35 ), 10720 ) that used our earlier MembStruk prediction methodology.

Effects of 5-Hydroxytryptamine Class 2 Receptor Antagonists on Bronchoconstriction and Pulmonary Remodeling Processes

Serotonin [5-hydroxytryptamine (5-HT)] is associated with several chronic pulmonary diseases, recognizing 5-HT₂ receptor antagonists as potential inhibitors of tissue remodeling. However, the effects of 5-HT₂ receptors, especially 5-HT_2B receptors on airway function and remodeling, are unclear. We investigated the role of 5-HT_2B receptors on airway smooth muscle contractility and remodeling processes. Murine precision-cut lung slices were pretreated with 5-HT_2B receptor antagonists (EXT5, EXT9, RS 127445, and PRX 08066), as well as ketanserin (5-HT_2A/2C receptor antagonist) (1, 10 μmol/L), before addition of cumulative concentrations of 5-HT to induce bronchoconstriction. Remodeling effects after treatment with 10 μmol/L 5-HT and 5-HT₂ receptor antagonists were further studied in distal lung tissue by examining release of profibrotic transforming growth factor (TGF)-β1 and proliferation of human bronchial smooth muscle cells (HBSMCs). 5-HT-induced bronchoconstriction was significantly reduced by EXT5, EXT9, and ketanserin, but not by RS 127445 or PRX 08066. The 5-HT_2B receptor antagonists significantly reduced TGF-β1 release. 5-HT, in combination with TGF-β1, increased proliferation of HBSMCs, a process reduced by EXT5 and EXT9. Our results indicate that EXT5 and EXT9 may relieve bronchoconstriction in murine airways and serve as an add-on effect in attenuating pulmonary remodeling by improving airway function. The antiproliferative effect on HBSMCs and the inhibition of TGF-β1 release further support a role of 5-HT_2B receptors in pathologic remodeling processes.

Predicting glycosaminoglycan surface protein interactions and implications for studying axonal growth

Cell-surface carbohydrates play important roles in numerous biological processes through their interactions with various protein-binding partners. These interactions are made possible by the vast structural diversity of carbohydrates and the diverse array of carbohydrate presentations on the cell surface. Among the most complex and important carbohydrates are glycosaminoglycans (GAGs), which display varied stereochemistry, chain lengths, and patterns of sulfation. GAG-protein interactions participate in neuronal development, angiogenesis, spinal cord injury, viral invasion, and immune response. Unfortunately, little structural information is available for these complexes; indeed, for the highly sulfated chondroitin sulfate motifs, CS-E and CS-D, there are no structural data. We describe here the development and validation of the GAG-Dock computational method to predict accurately the binding poses of protein-bound GAGs. We validate that GAG-Dock reproduces accurately (<1-Å rmsd) the crystal structure poses for four known heparin-protein structures. Further, we predict the pose of heparin and chondroitin sulfate derivatives bound to the axon guidance proteins, protein tyrosine phosphatase σ (RPTPσ), and Nogo receptors 1-3 (NgR1-3). Such predictions should be useful in understanding and interpreting the role of GAGs in neural development and axonal regeneration after CNS injury.

Molecular-Docking-Based Drug Design and Discovery

Currently 30-50% of drug targets are G Protein-Coupled Receptors (GPCRs). However, the clinical useful drugs for targeting GPCR have been limited by the lack of subtype selectivity or efficacy, leading to undesirable side effects. To develop subtype-selective GPCR ligands with desired molecular properties, better understanding is needed of the pharmacophore elements and of the binding mechanism required for subtype selectivity. To illustrate these issues, we describe here three successful applications to understand the binding mechanism associated with subtype selectivity: 5-HT2B (5-Hydroxytryptamine, 5-HT) serotonin receptor (HT2BR), H3 histamine receptor (H3HR) and A3 adenosine receptor (A3AR). The understanding of structure-function relationships among individual types and subtypes of GPCRs gained from such computational predictions combined with experimental validation and testing is expected the development of new highly selective and effective ligands to address such diseases while minimizing side-effects.

Computational Prediction and Biochemical Analyses of New Inverse Agonists for the CB1 Receptor

Human cannabinoid type 1 (CB1) G-protein coupled receptor is a potential therapeutic target for obesity. The previously predicted and experimentally validated ensemble of ligand-free conformations of CB1 [Scott, C. E. et al. Protein Sci. 2013 , 22 , 101 - 113 ; Ahn, K. H. et al. Proteins 2013 , 81 , 1304 - 1317] are used here to predict the binding sites for known CB1-selective inverse agonists including rimonabant and its seven known derivatives. This binding pocket, which differs significantly from previously published models, is used to identify 16 novel compounds expected to be CB1 inverse agonists by exploiting potential new interactions. We show experimentally that two of these compounds exhibit inverse agonist properties including inhibition of basal and agonist-induced G-protein coupling activity, as well as an enhanced level of CB1 cell surface localization. This demonstrates the utility of using the predicted binding sites for an ensemble of CB1 receptor structures for designing new CB1 inverse agonists.

Similarities between the Binding Sites of SB-206553 at Serotonin Type 2 and Alpha7 Acetylcholine Nicotinic Receptors: Rationale for Its Polypharmacological Profile

Evidence from systems biology indicates that promiscuous drugs, i.e. those that act simultaneously at various protein targets, are clinically better in terms of efficacy, than those that act in a more selective fashion. This has generated a new trend in drug development called polypharmacology. However, the rational design of promiscuous compounds is a difficult task, particularly when the drugs are aimed to act at receptors with diverse structure, function and endogenous ligand. In the present work, using docking and molecular dynamics methodologies, we established the most probable binding sites of SB-206553, a drug originally described as a competitive antagonist of serotonin type 2B/2C metabotropic receptors (5-HT2B/2CRs) and more recently as a positive allosteric modulator of the ionotropic α7 nicotinic acetylcholine receptor (nAChR). To this end, we employed the crystal structures of the 5-HT2BR and acetylcholine binding protein as templates to build homology models of the 5-HT2CR and α7 nAChR, respectively. Then, using a statistical algorithm, the similarity between these binding sites was determined. Our analysis showed that the most plausible binding sites for SB-206553 at 5-HT2Rs and α7 nAChR are remarkably similar, both in size and chemical nature of the amino acid residues lining these pockets, thus providing a rationale to explain its affinity towards both receptor types. Finally, using a computational tool for multiple binding site alignment, we determined a consensus binding site, which should be useful for the rational design of novel compounds acting simultaneously at these two types of highly different protein targets.

The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

Metabolic kinetics of 5-hydroxytryptamine and the research targets of functional gastrointestinal disorders

5-Hydroxytryptamine (5-HT) is an important neurotransmitter in both the central and enteric nervous systems. It has diverse functions in regulating gastrointestinal motility and visceral sensitivity, emotion, appetite, pain and sensory perception, cognition, sexual activity and sleep. These functions are mainly associated with the metabolic kinetics of 5-HT in different tissues. Tryptophan hydroxylase is the rate-limiting enzyme and modulates serotonin synthesis. Vesicular monoamine transporter 1 plays a role in 5-HT storage and release. Degradation of 5-HT is mediated by monoamine oxidase-A. All these factors influence the action of 5-HT in vivo. Functional gastrointestinal disorders (FGIDs) are characterized by a series of symptoms including abdominal pain, diarrhea, constipation, anxiety and depression, in the absence of identifiable structural or biochemical abnormalities. They are frequently accompanied by changed gut motility or visceral sensitivity. An increasing body of research has found FGIDs to be closely associated with 5-HT, and drugs such as citalopram, paroxetine, venlafaxine, alosetron, tegaserod, prucalopride and mosapride have all been developed or discovered from the perspective of the metabolic kinetics of 5-HT. This review discusses the relationship between the metabolic kinetics of 5-HT and research targets in the field of FGIDs and suggests areas of future study that may be useful for understanding these disorders and identification of potential therapeutic targets.

Predicted 3D structures of olfactory receptors with details of odorant binding to OR1G1

Olfactory receptors (ORs) are responsible for mediating the sense of smell; they allow humans to recognize an enormous number of odors but the connection between binding and perception is not known. We predict the ensemble of low energy structures for the human OR1G1 (hOR1G1) and also for six other diverse ORs, using the G protein-coupled receptor Ensemble of Structures in Membrane BiLayer Environment complete sampling method that samples 13 trillion different rotations and tilts using four different templates to predict the 24 structures likely to be important in binding and activation. Our predicted most stable structures of hOR1G1 have a salt-bridge between the conserved D3.49 and K6.30 in the D(E)RY region, that we expect to be associated with an inactive form. The hOR1G1 structure also has specific interaction in transmembrane domains (TMD) 3-6 (E3.39 and H6.40), which is likely an important conformational feature for all hORs because of the ~94 to 98 % conservation among all hOR sequences. Of the five ligands studied (nonanal, 9-decen-1-ol, 1-nonanol, camphor, and n-butanal), we find that the 4 expected to bind lead to similar binding energies with nonanol the strongest.

Predicted ligands for the human urotensin-II G protein-coupled receptor with some experimental validation

Human Urotensin-II (U-II) is the most potent mammalian vasoconstrictor known.1 Thus, a U-II antagonist would be of therapeutic value in a number of cardiovascular disorders.2 Here, we describe our work on the prediction of the structure of the human U-II receptor (hUT2 R) using GEnSeMBLE (GPCR Ensemble of Structures in Membrane BiLayer Environment) complete sampling Monte Carlo method. With the validation of our predicted structures, we designed a series of new potential antagonists predicted to bind more strongly than known ligands. Next, we carried out R-group screening to suggest a new ligand predicted to bind with 7 kcal mol(-1) better energy than 1-{2-[4-(2-bromobenzyl)-4-hydroxypiperidin-1-yl]ethyl}-3-(thieno[3,2-b]pyridin-7-yl)urea, the designed antagonist predicted to have the highest affinity for the receptor. Some of these predictions were tested experimentally, validating the computational results. Using the pharmacophore generated from the predicted structure for hUT2 R bound to ACT-058362, we carried out virtual screening based on this binding site. The most potent hit compounds identified contained 2-(phenoxymethyl)-1,3,4-thiadiazole core, with the best derivative exhibiting an IC50 value of 0.581 μM against hUT2 R when tested in vitro. Our efforts identified a new scaffold as a potential new lead structure for the development of novel hUT2 R antagonists, and the computational methods used could find more general applicability to other GPCRs.

Insights into the influence of 5-HT2c aminoacidic variants with the inhibitory action of serotonin inverse agonists and antagonists

Specific modulation of serotonin 5-HT(2C) G protein-coupled receptors may be therapeutic for obesity and neuropsychiatric disorders. The different efficacy of drugs targeting these receptors are due to the presence of genetic variants in population and this variability is still hard to predict. Therefore, in order to administer the more suitable drug, taking into account patient genotype, it is necessary to know the molecular effects of its gene nucleotide variations. In this work, starting from an accurate 3D model of 5-HT(2C), we focus on the prediction of the possible effect of some single nucleotide polymorphisms (SNPs) producing amino acidic changes in proximity of the 5-HT(2C) ligand binding site. Particularly we chose a set of 5-HT(2C) inverse agonists and antagonists which have high inhibitory activity. After prediction of the structures of the receptor-ligand complexes using molecular docking tools, we performed full atom molecular dynamics simulations in explicit lipid bilayer monitoring the interactions between ligands and trans-membrane helices of the receptor, trying to infer relations with their biological activity. Serotonin, as the natural ligand was chosen as reference compound to advance a hypothesis able to explain the receptor inhibition mechanism. Indeed we observed a different behavior between the antagonists and inverse agonist with respect to serotonin or unbounded receptor, which could be responsible, even if not directly, of receptor's inactivation. Furthermore, we analyzed five aminoacidic variants of 5HT(2C) receptor observing alterations in the interactions between ligands and receptor which give rise to changes of free energy values for every complex considered.

Predictive in silico studies of human 5-hydroxytryptamine receptor subtype 2B (5-HT2B) and valvular heart disease

Serotonin (5-hydroxytryptamine, 5-HT) receptors are neuromodulator neurotransmitter receptors which when activated trigger a signal transduction cascade within cells resulting in cell-cell communication. 5-hydroxytryptamine receptor 2B (5-HT2B) is a subtype of the seven members of 5-hydroxytrytamine receptors family which is the largest member of the super family of 7-transmembrane G-protein coupled receptors (GPCRs). Not only do 5-HT receptors play physiological roles in the cardiovascular system, gastrointestinal and endocrine function as well as the central nervous system, but they also play a role in behavioral functions. In particular 5-HT2B receptor is widely spread with regards to its distribution throughout bodily tissues and is expressed at high levels in the lungs, peripheral tissues, liver, kidneys and prostate, just to name a few. Hence 5-HT2B participates in multiple biological functions including CNS regulation, regulation of gastrointestinal motality, cardiovascular regulation and 5-HT transport system regulation. While 5-HT2B is a viable drug target and has therapeutic indications for treating obesity, psychosis, Parkinson's disease etc. there is a growing concern regarding adverse drug reactions, specifically valvulopathy associated with 5-HT2B agonists. Due to the sequence homology experienced by 5-HT2 subtypes there is also a concern regarding the off-target effects of 5-HT2A and 5-HT2C agonists. The concepts of sensitivity and subtype selectivity are of paramount importance and now can be tackled with the aid of in silico studies, especially cheminformatics, to develop models to predict valvulopathy associated toxicity of drug candidates prior to clinical trials. This review has highlighted three in silico approaches thus far that have been successful in either predicting 5-HT2B toxicity of molecules or identifying important interactions between 5-HT2B and drug molecules that bring about valvulopathy related toxicities.

SuperBiHelix method for predicting the pleiotropic ensemble of G-protein-coupled receptor conformations

There is overwhelming evidence that G-protein-coupled receptors (GPCRs) exhibit several distinct low-energy conformations, each of which might favor binding to different ligands and/or lead to different downstream functions. Understanding the function of such proteins requires knowledge of the ensemble of low-energy configurations that might play a role in this pleiotropic functionality. We earlier reported the BiHelix method for efficiently sampling the (12)(7) = 35 million conformations resulting from 30° rotations about the axis (η) of all seven transmembrane helices (TMHs), showing that the experimental structure is reliably selected as the best conformation from this ensemble. However, various GPCRs differ sufficiently in the tilts of the TMHs that this method need not predict the optimum conformation starting from any other template. In this paper, we introduce the SuperBiHelix method in which the tilt angles (θ, ϕ) are optimized simultaneously with rotations (η) efficiently enough that it is practical and sufficient to sample (5 × 3 × 5)(7) = 13 trillion configurations. This method can correctly identify the optimum structure of a GPCR starting with the template from a different GPCR. We have validated this method by predicting known crystal structure conformations starting from the template of a different protein structure. We find that the SuperBiHelix conformational ensemble includes the higher energy conformations associated with the active protein in addition to those associated with the more stable inactive protein. This methodology was then applied to design and experimentally confirm structures of three mutants of the CB1 cannabinoid receptor associated with different functions.

Studies on the interactions between β2 adrenergic receptor and Gs protein by molecular dynamics simulations

The β2 adrenergic receptor (β2AR) plays a key role in the control of smooth muscle relaxation in airways, the therapy of asthma, and a series of other basic physiological functions. Recently, the crystal structure of the β2AR-Gs protein complex was reported, which facilitates study of the activation mechanism of the β2AR and G-protein-coupled receptors (GPCRs). In this work, we perform 20 ns molecular dynamics (MD) simulations of the β2AR-Gs protein complex with its agonist in an explicit lipid and water environment to investigate the activation mechanism of β2AR. We find that during 20 ns MD simulation with a nanobody bound the interaction between the β2AR and the Gs protein is stable and the whole system is equilibrated within 6 ns. However, without a nanobody stabilizing the complex, the agonist triggers conformational changes of β2AR sequentially from the extracellular region to the intracellular region, especially the intracellular parts of TM3, TM5, TM6, and TM7, which directly interact with the Gs protein. Our results show that the β2AR-Gs protein complex makes conformational changes in the following sequence: (1) an agonist-bound part of β2AR, (2) the intracellular region of β2AR, and (3) the Gs protein.

Computational methods for the discovery of mood disorder therapies

INTRODUCTION

Despite the significant progress, research is still needed to reveal details of the complex and dynamic chemical processes operating in the central nervous system (CNS) and their relationship to psychological effects such as mood disorders. The incidence of behavioral depression is widely spread worldwide, with an estimated 14.8 million adults diagnosed yearly in the United States alone. The efficacy of current antidepressants on 50 - 60% of patients, their slow onset of action and the prevalence of adverse side effects highlight the need for developing a new generation of improved antidepressants. Computational methods have the potential to aid in the discovery of mood modulators.

AREAS COVERED

This review contains three main sections: historical evolution of marketed antidepressants, physicochemical and structural properties of antidepressant compounds reported in the ChEMBL database and recent efforts in the design and discovery of antidepressants using computational methods. The authors provide details of the computational methods employed, from chemoinformatic analyses to molecular modeling.

EXPERT OPINION

While there have been numerous and important findings in depression research, the high cost and time spent on research into new therapies for brain disorders is a risky undertaking. Computational methodologies can be employed to speed up the discovery of new antidepressants and to detect new sources of chemical compounds with potential antidepressant activity. Compound collections containing compounds already approved in the pharmaceutical and food industries that cover the property space and complement the structural space of CNS drugs represent a promising starting point for the discovery of new antidepressant agents.