A 3D-QSAR study on the structural requirements for binding to CB(1) and CB(2) cannabinoid receptors

Development of a membrane-based Gi-CASE biosensor assay for profiling compounds at cannabinoid receptors

Introduction: The cannabinoid receptor (CBR) subtypes 1 (CB1R) and 2 (CB2R) are key components of the endocannabinoid system (ECS), playing a central role in the control of peripheral pain, inflammation and the immune response, with further roles in the endocrine regulation of food intake and energy balance. So far, few medicines targeting these receptors have reached the clinic, suggesting that a better understanding of the receptor signalling properties of existing tool compounds and clinical candidates may open the door to the development of more effective and safer treatments. Both CB1R and CB2R are Gαi protein-coupled receptors but detecting Gαi protein signalling activity reliably and reproducibly is challenging. This is due to the inherent variability in live cell-based assays and restrictions around the use of radioactive [35S]-GTPγS, a favoured technology for developing higher-throughput membrane-based Gαi protein activity assays. Methods: Here, we describe the development of a membrane-based Gαi signalling system, produced from membrane preparations of HEK293TR cells, stably overexpressing CB1R or CB2R, and components of the Gαi-CASE biosensor. This BRET-based system allows direct detection of Gαi signalling in both cells and membranes by monitoring bioluminescence resonance energy transfer (BRET) between the α and the βγ subunits. Cells and membranes were subject to increasing concentrations of reference cannabinoid compounds, with 10 μM furimazine added to generate RET signals, which were detected on a PHERAstar FSX plate reader, then processed using MARS software and analysed in GraphPad PRISM 9.2. Results: In membranes expressing the Gi-CASE biosensor, the cannabinoid ligands profiled were found to show agonist and inverse agonist activity. Agonist activity elicited a decrease in the BRET signal, indicative of receptor activation and G protein dissociation. Inverse agonist activity caused an increase in BRET signal, indicative of receptor inactivation, and the accumulation of inactive G protein. Our membrane-based Gi-CASE NanoBRET system successfully characterised the potency (pEC50) and efficacy (Emax) of CBR agonists and inverse agonists in a 384-well screening format. Values obtained were in-line with whole-cell Gi-CASE assays and consistent with literature values obtained in the GTPγS screening format. Discussion: This novel, membrane-based Gαi protein activation assay is applicable to other Gαi-coupled GPCRs, including orphan receptors, allowing real-time higher-throughput measurements of receptor activation.

Machine Learning and Computational Chemistry for the Endocannabinoid System

Computational methods in medicinal chemistry facilitate drug discovery and design. In particular, machine learning methodologies have recently gained increasing attention. This chapter provides a structured overview of the current state of computational chemistry and its applications for the interrogation of the endocannabinoid system (ECS), highlighting methods in structure-based drug design, virtual screening, ligand-based quantitative structure-activity relationship (QSAR) modeling, and de novo molecular design. We emphasize emerging methods in machine learning and anticipate a forecast of future opportunities of computational medicinal chemistry for the ECS.

The use of a quantitative structure-activity relationship (QSAR) model to predict GABA-A receptor binding of newly emerging benzodiazepines

The illicit market for new psychoactive substances is forever expanding. Benzodiazepines and their derivatives are one of a number of groups of these substances and thus far their number has grown year upon year. For both forensic and clinical purposes it is important to be able to rapidly understand these emerging substances. However as a consequence of the illicit nature of these compounds, there is a deficiency in the pharmacological data available for these 'new' benzodiazepines. In order to further understand the pharmacology of 'new' benzodiazepines we utilised a quantitative structure-activity relationship (QSAR) approach. A set of 69 benzodiazepine-based compounds was analysed to develop a QSAR training set with respect to published binding values to GABA_A receptors. The QSAR model returned an R² value of 0.90. The most influential factors were found to be the positioning of two H-bond acceptors, two aromatic rings and a hydrophobic group. A test set of nine random compounds was then selected for internal validation to determine the predictive ability of the model and gave an R² value of 0.86 when comparing the binding values with their experimental data. The QSAR model was then used to predict the binding for 22 benzodiazepines that are classed as new psychoactive substances. This model will allow rapid prediction of the binding activity of emerging benzodiazepines in a rapid and economic way, compared with lengthy and expensive in vitro/in vivo analysis. This will enable forensic chemists and toxicologists to better understand both recently developed compounds and prediction of substances likely to emerge in the future.

Three-dimensional quantitative structure-selectivity relationships analysis guided rational design of a highly selective ligand for the cannabinoid receptor 2

This paper describes a three-dimensional quantitative structure-selectivity relationships (3D-QSSR) study for selectivity of a series of ligands for cannabinoid CB1 and CB2 receptors. 3D-QSSR exploration was expected to provide design information for drugs with high selectivity toward the CB2 receptor. The proposed 3D computational model was performed by Phase and generated taking into account a number of structurally diverse compounds characterized by a wide range of selectivity index values. The model proved to be predictive, with r2 of 0.95 and Q2 of 0.63. In order to get prospective experimental validation, the selectivity of an external data set of 39 compounds reported in the literature was predicted. The correlation coefficient (r2=0.56) obtained on this unrelated test set provided evidence that the correlation shown by the model was not a chance result. Subsequently, we essayed the ability of our approach to help the design of new CB2-selective ligands. Accordingly, based on our interest in studying the cannabinergic properties of quinolones, the N-(adamantan-1-yl)-4-oxo-8-methyl-1-pentyl-1,4-dihydroquinoline-3-carboxamide (65) was considered as a potential synthetic target. The log(SI) value predicted by using our model was indicative of high CB2 selectivity for such a compound, thus spurring us to synthesize it and to evaluate its CB1 and CB2 receptor affinity. Compound 65 was found to be an extremely selective CB2 ligand as it displayed high CB2 affinity (Ki=4.9 nM), while being devoid of CB1 affinity (Ki>10,000 nM). The identification of a new selective CB2 receptor ligand lends support for the practicability of quantitative ligand-based selectivity models for cannabinoid receptors. These drug discovery tools might represent a valuable complementary approach to docking studies performed on homology models of the receptors.

Identification of novel cannabinoid CB1 receptor antagonists by using virtual screening with a pharmacophore model

CB1 receptor antagonists have proven to be clinically effective in treating obesity and related disorders. We report here the identification of a novel class of azetidinone CB1 antagonists by using virtual screening methods. For this purpose, we developed a pharmacophore model based on known representative CB1 antagonists and employed it to screen a database of about a half million Schering-Plough compounds. We applied a stepwise filtering protocol based on molecular weight, compound availability, and a modified rule-of-five to reduce the number of hits. We then combined Bayesian modeling and clustering techniques to select a final set of 420 compounds for in vitro testing. Five compounds were found to have >50% inhibition at 100 nM in a CB1 competitive binding assay and were further characterized by using both CB1 and CB2 assays. The most potent compound has a CB1 K i of 53 nM and >5-fold selectivity against the CB2 receptor.

The Application of 3D-QSAR Studies for Novel Cannabinoid Ligands Substituted at the C1‘ Position of the Alkyl Side Chain on the Structural Requirements for Binding to Cannabinoid Receptors CB1 and CB2

A set of 30 novel Delta8-tetrahydrocannabinol and cannabidiol analogues were subjected to three-dimensional quantitative structure-activity relationship studies using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. Using a combination of molecular modeling techniques and NMR spectroscopy, the putative bioactive conformation of the most potent cannabinoid (CB) ligand in the training set was determined. This conformer was used as the template and CB1 and CB2 pharmacophore models were developed. These models were fitted with experimental binding data and gave high correlation coefficients. Contour maps of the CB1 and CB2 models of CoMFA and CoMSIA approaches show that steric effects dominantly determine the binding affinities. The CoMFA and CoMSIA analyses based on the binding affinity data of CB ligands at the CB1 and CB2 receptors allowed us to deduce the possible optimal binding positions. This information can be used for the design of new CB analogues with enhanced activity and other tailored properties.

Quantitative structure−activity relationship (QSAR) for neuroprotective activity of terpenoids

Neuroprotective activity of thirteen terpenoids on human neuroblastoma SH-SY5Y was evaluated in vitro by using a simulated ischemia model. The protective effects on ischemic damage ranged from 3.0% to 56.5%, and trans-4,11,11-trimethyl-8-methylenebicyclo[7,2,0]undec-4-ene (trans-caryophyllene) showed the highest neuroprotective activity. A quantitative structure-activity relationship (QSAR) model was developed for eleven terpenoids with significant neuroprotective activity using TSAR software. The QSAR study produced two equations with significant predictive values (r(2) and p value) and indicated that the activity was mainly governed by lipophilicity, shape index, and electrostatic property. This QSAR approach can contribute to a better understanding of structural properties of the terpenoids responsible for neuroprotection, and can be useful in predicting the neuroprotective activity of other terpenoids.

Comparative Binding Energy Analysis Considering Multiple Receptors: A Step toward 3D-QSAR Models for Multiple Targets

Comparative binding energy analysis, a technique to derive receptor-based three-dimensional quantitative structure-activity relationships (3D-QSAR), is herein extended to consider both affinity and selectivity in the derivation of the QSAR model. The extension is based on allowing multiple structurally related receptors to enter the X-matrix employed in the derivation of the structure-activity model. As a result, a single model common to all of them is obtained that considers both intra- and inter-receptor affinity differences for a given congeneric series. We applied the technique to a series of 88 3-amidinophenylalanines, binding to thrombin, trypsin, and factor Xa (fXa). A single predictive regression model for the three receptors involving 202 complexes, with a leave-one out (LOO) cross-validated Q(2) of 0.689, was obtained, and selectivity requirements were investigated. We find that total or partial occupancy of any of the three main pockets in the binding site (D-site, P-site, and the rim of the S1-site) leads to higher affinity across the family. However, the fact that thrombin can make stronger interactions in the P-site, as a result of its exclusive 60-loop, makes of this site a specificity pocket for this thrombin. Occupancy of the D-site leads to more active inhibitors toward fXa for the same reason, but the model does not highlight strongly the D-box because inhibitors are too short to fully occupy it. Negative charge density in the neighborhood of position 88 (a Lys insertion in thrombin) is found to be a determinant for thrombin recognition. These results were consistent with previous studies on selectivity in the thrombin/trypsin/fXa system.

3D-QSAR Studies of Arylpyrazole Antagonists of Cannabinoid Receptor Subtypes CB1 and CB2. A Combined NMR and CoMFA Approach

The present work focuses on the study of the three-dimensional (3D) structural requirements for selective antagonist activity of arylpyrazole compounds at the cannabinoid CB1 and CB2 receptors. Initially, a combined high-resolution two-dimensional (2D) NMR and computer modeling approach was carried out to study the solution structure of the key pyrazole derivative N-(piperidin-1-yl)-5-phenyl-1-(n-pentyl)-4-methyl-1H-pyrazole-3-carboxamide (AM263). By using the NMR-determined molecular conformers as templates, the 3D quantitative structure-activity relationship (QSAR) studies were performed with the comparative molecular field analysis (CoMFA) approach on a set of arylpyrazole cannabinoid receptor antagonists. Molecular alignments suitable for deriving valuable pharmacophoric features for this series of compounds were determined. Such systematic 3D-QSAR/CoMFA analyses of 29 molecules and their receptor affinities gave guidance for understanding the binding affinities of arylpyrazoles at the CB1 and CB2 binding sites, respectively. Comparison of CoMFA steric and potential contour maps for affinity at the two cannabinoid receptor subtypes helps to differentiate structural requirements for each subtype and serves as a basis for the design of later-generation analogues.

3D-QSAR Studies on Cannabinoid CB1 Receptor Agonists: G-Protein Activation as Biological Data

G-protein activation via the CB1 receptor was determined for a group of various CB1 ligands and utilized as biological activity data in subsequent CoMFA and CoMSIA studies. Both manual techniques and automated docking at CB1 receptor models were used to obtain a common alignment of endocannabinoid and classical cannabinoid derivatives. In the final alignment models, the endocannabinoid headgroup occupies a unique region distinct from the classical cannabinoid structures, supporting the hypothesis that these structurally diverse molecules overlap only partially within the receptor binding site. Both CoMFA and CoMSIA produce statistically significant models based on the manual alignment and a docking alignment at one receptor conformer. Leave-half-out cross-validation and progressive scrambling were successfully used in assessing the predictivity of the QSAR models.

Synthesis of long-chain amide analogs of the cannabinoid CB1 receptor antagonist N-(piperidinyl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide (SR141716) with unique binding selectivities and pharmacological activities

An extended series of alkyl carboxamide analogs of N-(piperidinyl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl- 1H-pyrazole-3-carboxamide (SR141716; 5) was synthesized. Each compound was tested for its ability to displace the prototypical cannabinoid ligands ([3H]CP-55,940, [3H]2; [3H]SR141716, [3H]5; and [3H]WIN55212-2, [3H]3), and selected compounds were further characterized by determining their ability to affect guanosine 5'-triphosphate (GTP)-gamma-[35S] binding and their effects in the mouse vas deferens assay. This systematic evaluation has resulted in the discovery of novel compounds with unique binding properties at the central cannabinoid receptor (CB1) and distinctive pharmacological activities in CB1 receptor tissue preparations. Specifically, compounds with nanomolar affinity which are able to fully displace [3H]5 and [3H]2, but unable to displace [3H]3 at similar concentrations, have been synthesized. This selectivity in ligand displacement is unprecedented, in that previously, compounds in every structural class of cannabinoid ligands had always been shown to displace each of these radioligands in a competitive fashion. Furthermore, the selectivity of these compounds appears to impart unique pharmacological properties when tested in a mouse vas deferens assay for CB1 receptor antagonism.

3-Indolyl-1-naphthylmethanes: new cannabimimetic indoles provide evidence for aromatic stacking interactions with the CB(1) cannabinoid receptor

A series of 1-pentyl-1H-indol-3-yl-(1-naphthyl)methanes (9-11) and 2-methyl-1-pentyl-1H-indol-3-yl-(1-naphthyl)methanes (12-14) have been synthesized to investigate the hypothesis that cannabimimetic 3-(1-naphthoyl)indoles interact with the CB(1) receptor by hydrogen bonding to the carbonyl group. Indoles 9-11 have significant (K(i)=17-23nM) receptor affinity, somewhat less than that of the corresponding naphthoylindoles (5, 15, 16). 2-Methyl-1-indoles 12-14 have little affinity for the CB(1) receptor, in contrast to 2-methyl-3-(1-naphthoyl)indoles 17-19, which have affinities comparable to those of 5, 15, 16. A cannabimimetic indene hydrocarbon (26) was synthesized and found to have K(i)=26+/-4nM. Molecular modeling and receptor docking studies of naphthoylindole 16, its 2-methyl congener (19) and indolyl-1-naphthylmethanes 11 and 14, combined with the receptor affinities of these cannabimimetic indoles, strongly suggest that these cannabinoid receptor ligands bind primarily by aromatic stacking interactions in the transmembrane helix 3-4-5-6 region of the CB(1) receptor.

Tricyclic pyrazoles. Part 1: synthesis and biological evaluation of novel 1,4-dihydroindeno[1,2-c]pyrazol-based ligands for CB1and CB2 cannabinoid receptors

Cannabinoids receptors, cellular elements of the endocannabinoid system, have been the focus of extensive studies because of their potential functional role in several important physiological and pathological processes. To further evaluate the properties of CB receptors, especially CB(1) and CB(2) subtypes, we have designed, using SR141716A as a benchmark, a new series of rigid 1-aryl-1,4-dihydroindeno[1,2-c]pyrazole-3-carboxamides. Compounds 1 were synthesized from substituted 1-aryl-1,4-dihydroindeno[1,2-c]pyrazole-3-carboxylic acids and requisite amines. The various analogues were assayed for binding both to the brain and peripheral cannabinoid receptors (CB(1) and CB(2)). Seven of the new compounds displayed very high in vitro CB(2) binding affinities, especially 1a, 1b, 1c, 1e, 1g, 1h and 1j which showed K(i) values of 0.34, 0.225, 0.27, 0.23, 0.385, 0.037 and 0.9 nM, respectively. Compounds 1a, 1b, 1c and 1h showed the highest selectivity for CB(2) receptor with K(i)(CB(1)) to K(i)(CB(2)) ratios of 6029, 5635, 5814 and 9810, respectively. Noticeably, 1h exhibited the highest affinity and selectivity for CB(2) receptors.

Oxygenated metabolites of anandamide and 2-arachidonoylglycerol: conformational analysis and interaction with cannabinoid receptors, membrane transporter, and fatty acid amide hydrolase

This study was aimed at finding structural requirements for the interaction of the acyl chain of endocannabinoids with cannabinoid receptors, membrane transporter protein, and fatty acid amide hydrolase (FAAH). To this end, the flexibility of the acyl chain was restricted by introduction of an 1-hydroxy-2Z,4E-pentadiene system in anandamide (N-arachidonoylethanolamine, AEA) and 2-arachidonoylglycerol (2-AG) at various positions using different lipoxygenases. This brought about selectivity and attenuated the binding potency of AEA and 2-AG. Although the displacement constants were modest, 15(S)-hydroxy-eicosa-5Z,8Z,11Z,13E-tetraenoyl-N-(2-hydroxyethyl)amine was found to bind selectively to the CB(1) receptor, whereas its 1-arachidonoyl-sn-glycerol analogue and 13(S)-hydroxy-octadeca-9Z,11E-dienoyl-N-(2-hydroxyethyl)amine could selectively bind to the CB(2) receptor. 11(S)-Hydroxy-eicosa-5Z,8Z,12E,14Z-tetraenoyl-N-(2-hydroxyethyl)amine did not bind to either receptor, whereas 12(S)-hydroxy-eicosa-5Z,8Z,10E,14Z-tetraenoyl-N-(2-hydroxyethyl)amine did bind to both CB receptors with an affinity similar to that of AEA. All oxygenated anandamide derivatives were good inhibitors of FAAH (low micromolar K(i)) but were ineffective on the AEA transporter. 2-AG rapidly isomerizes into 1(3)-arachidonoyl-sn-glycerol. Both 1- and 3-arachidonoyl-sn-glycerol did not bind to either CB receptor and did not interfere with AEA transport. Thus, after it is isomerized, 2-AG is inactivated, thereby decreasing effective concentrations of 2-AG. Analysis of (1)H NMR spectra revealed that chloroform did not induce notably different conformations in the acyl chain of 15(S)-hydroxy-eicosa-5Z,8Z,11Z,13E-tetraenoic acid as compared with water. Molecular dynamics (MD) simulations of AEA and its analogues in the presence of explicit water molecules revealed that a tightly folded conformation of the acyl chain is not the only requirement for CB(1) binding. Structural details of the C(2)-C(15) loop, such as an sp(2) carbon at position 11, are necessary for receptor binding. The MD simulations may suggest that the average orientations of the pentyl tail of AEA and 12(S)-hydroxy-eicosa-5Z,8Z,10E,14Z-tetraenoyl-N-(2-hydroxyethyl)amine are different from that of the low-affinity, inactive ligands.

Functional versus chemical diversity: is biodiversity important for drug discovery?

Prospecting the full biodiversity of nature to find leads for new drugs is not necessary. Because finding leads is aimed at identifying biological activity, structure is of secondary importance. Furthermore, although natural chemical diversity might be unrivalled, functional diversity is bound to be considerably less. It is likely that many millions of chemically distinct molecules exist in nature but it is inconceivable that the number of different biological functions is near this number. This is corroborated by knowledge obtained from the genome sequences of an increasing number of species. It is unlikely that ligands for specific molecular targets are restricted to one species and even individual compounds are often found in more than one species. Important molecular mechanisms are likely to be ubiquitous and there are no a priori reasons to assume that some are restricted to, for example, tropical rainforests. Thus, there are no obvious advantages of "biodiversity prospecting", which will, possibly, endanger fragile ecosystems in the search for rare species.

Exploration of the pharmacophore of 3-alkyl-5-arylimidazolidinediones as new CB(1) cannabinoid receptor ligands and potential antagonists: synthesis, lipophilicity, affinity, and molecular modeling

A set of 29 3-alkyl 5-arylimidazolidinediones (hydantoins) with affinity for the human cannabinoid CB(1) receptor was studied for their lipophilicity and conformational properties in order to delineate a pharmacophore. These molecules constitute a new template for cannabinoid receptor recognition, since (a) their structure differs from that of classical cannabinoid ligands and (b) antagonism is the mechanism of action of at least three compounds (20, 21, and 23). Indeed, in the [(35)S]-GTP gamma S binding assay using rat cerebellum homogenates, they behave as antagonists without any inverse agonism component. Using a set of selected compounds, experimental lipophilicity was measured by RP-HPLC and calculated by a fragmental method (CLOGP) and a conformation-dependent method (CLIP based on the molecular lipophilicity potential). These approaches revealed two models which differentiate the binding mode of nonpolar and polar hydantoins and which could explain, at least for compounds 20, 21, and 23, the mechanism of action of this new family of cannabinoid ligands.

A three-dimensional quantitative structure-activity relationship study of heparin-binding epidermal growth factor shedding inhibitors using comparative molecular field analysis

Despite the lack of structural information on the heparin-binding (HB) epidermal growth factor (EGF) shedding putative target enzyme, the design of potent HB-EGF shedding inhibitors has been attempted by means of comparative molecular field analysis (CoMFA), a well-established 3D-QSAR technique. Two different binding modes, obtained by docking a flexible representative into the MMP-3 and TACE target enzymes, were considered as alignment rules for an in-house data set of 50 HB-EGF shedding inhibitors. CoMFA models were derived with the standard steric, electrostatic, and Bohacek and McMartin's H-bond molecular fields. These fields were used individually or in combination. For both alignments, the H-bond field alone yielded the best statistical models. From the analysis of the CoMFA contours, ideas for testing the size of the S1' pocket and suggestions for the design of new inhibitors came forward, resulting in the synthesis and testing of four new inhibitors. Three of four compounds turned out to possess from good (IC(50) = 0.56 and 0.60 microM) to excellent (IC(50) = 0.13 microM) inhibitory activity. The hypothesis that, upon binding, the S1' pocket in the vicinity of the R(1) benzene ring must be narrow in size was confirmed by the weak activity (IC(50) = 1.1 microM) of the fourth compound. The experimental profile of these new inhibitors does suggest the MMP-3 alignment as the most plausible one for HB-EGF shedding inhibitors.

A pyridone analogue of traditional cannabinoids. A new class of selective ligands for the CB(2) receptor

A pyridone analogue (5) of the potent bicyclic cannabinoid CP 47,497 (6) has been synthesized as a model for one conformational isomer of anandamide and to test the hypothesis that an amide carbonyl may serve as a hydrogen bond acceptor in interactions with the CB(1) cannabinoid receptor. Pyridone 5 was synthesized from 6-bromo-2-methoxypyridine (10) by palladium catalyzed coupling with 1-pentyne to provide 11. Catalytic hydrogenation of 11 and hydrolysis to pyridone 13 followed by N-alkylation gave 1-propyl-6-pentyl-2-pyridone (15). Bromination of 15 gave dibromide 18, which underwent Heck coupling with cyclohex-2-en-1-one to give enone 19. Catalytic hydrogenation of 19 gave ketone 20 which was reduced using NaBH(4) to alcohol 5. Reduction of 20 with K-Selectride gave the axial epimer of 5 (21). Neither alcohol 5 nor 21 have significant affinity for the CB(1) receptor (K(i) > 970 nM), but both have moderately high affinity for the CB(2) receptor (K(i) < 60 nM).

Attempts of ranking in a series of synthetic nonpsychotropic cannabinoids

Dexanabinol and other synthetic 6aS-trans cannabinoids are devoid of cannabimimetic activity, as they do not have affinity toward cannabinoid receptors. On the other hand, these compound bind to the NMDA receptor and possess neuroprotective properties. A ranking of 6aS-trans cannabinoids based on their NMDA receptor binding affinity and by using a variety of calculated properties included in a fully computerized expert system has been attempted. The results of the study indicate that either the present isosteric-isoelectronic-based ranking criteria is not adequate to reproduce NMDA receptor binding or that some other members of the series rather than dexanabinol are the true lead compounds of 6aS-trans cannabinoids.