Structure−Selectivity Investigations of D2-Like Receptor Ligands by CoMFA and CoMSIA Guiding the Discovery of D3 Selective PET Radioligands

Approach to the specificity and selectivity between D2 and D3 receptors by mutagenesis and binding experiments part I: Expression and characterization of D2 and D3 receptor mutants

D3/D2 sub-specificity is a complex problem to solve. Indeed, in the absence of easy structural biology of the G-protein coupled receptors, and despite key progresses in this area, the systematic knowledge of the ligand/receptor relationship is difficult to obtain. Due to these structural biology limitations concerning membrane proteins, we favored the use of directed mutagenesis to document a rational towards the discovery of markedly specific D3 ligands over D2 ligands together with basic binding experiments. Using our methodology of stable expression of receptors in HEK cells, we constructed the gene encoding for 24 mutants and 4 chimeras of either D2 or D3 receptors and expressed them stably. Those cell lines, expressing a single copy of one receptor mutant each, were stably constructed, selected, amplified and the membranes from them were prepared. Binding data at those receptors were obtained using standard binding conditions for D2 and D3 dopamine receptors. We generated 26 new molecules derived from D2 or D3 ligands. Using 8 reference compounds and those 26 molecules, we characterized their binding at those mutants and chimeras, exemplifying an approach to better understand the difference at the molecular level of the D2 and D3 receptors. Although all the individual results are presented and could be used for minute analyses, the present report does not discuss the differences between D2 and D3 data. It simply shows the feasibility of the approach and its potential.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Iron oxide encapsulated by copper-apatite: an efficient magnetic nanocatalyst for N-arylation of imidazole with boronic acid

N-Arylation of imidazole was carried out with various arylboronic acids on iron oxide encapsulated by copper-apatite (Fe3O4@Cu-apatite), producing excellent yields. Firstly, the iron nanoparticles were prepared using a solvothermal method, and then they were encapsulated by copper-apatite to obtain magnetic Fe3O4@Cu-apatite nanocatalysts. Several physico-chemical analysis techniques were used to characterize the prepared nanostructured Fe3O4@Cu-apatite catalyst. The prepared Fe3O4@Cu-apatite was used as a nanocatalyst for N-arylation of imidazole with a series of arylboronic acids with different substituents to reaffirm the effectiveness of this magnetic nanocatalyst. The Fe3O4@Cu-apatite nanocatalyst can also be easily separated from the reaction mixture using an external magnet. More importantly, the as-prepared Fe3O4@Cu-apatite exhibited good reusability and stability properties in successive cycles. However, there was a notable loss of its catalytic activity after multiple cycles.

Design, synthesis, and evaluation of bitopic arylpiperazine-phthalimides as selective dopamine D3 receptor agonists

The dopamine D3 receptor (D3R) is a proven therapeutic target for the treatment of neurological and neuropsychiatric disorders. In particular, D3R-selective ligands that can eliminate side effects associated with dopamine D2 receptor (D2R) therapeutics have been validated. However, the high homology in signaling pathways and the sequence similarity between D2R and D3R have rendered the development of D3R-selective ligands challenging. Herein, we designed and synthesized a series of piperazine-phthalimide bitopic ligands based on a fragment-based and molecular docking inspired design. Compound 9i was identified as the most selective D3R ligand among these bitopic ligands. Its selectivity was improved compared to reference compounds 1 and 2 by 9- and 2-fold, respectively, and it was 21-fold more potent than compound 2. Molecular docking demonstrated that the orientation of Leu2.64 and Phe7.39 and the packing at the junction of helices may affect the specificity for D3R over D2R. Functional evaluation revealed that D3R-selective ligand 9i displayed a subpicomolar agonist activity at D3R with a 199-fold increase in potency compared to quinpirole. These results may be useful for the fragment-based design of bitopic compounds as selective D3R ligands.

Site-selective Suzuki-Miyaura coupling of heteroaryl halides - understanding the trends for pharmaceutically important classes

Suzuki-Miyaura cross-coupling reactions of heteroaryl polyhalides with aryl boronates are surveyed. Drawing on data from literature sources as well as bespoke searches of Pfizer's global chemistry RKB and CAS Scifinder® databases, the factors that determine the site-selectivity of these reactions are discussed with a view to rationalising the trends found.

Predicting subtype selectivity of dopamine receptor ligands with three-dimensional biologically relevant spectrum

We applied a novel molecular descriptor, three-dimensional biologically relevant spectrum (BRS-3D), in subtype selectivity prediction of dopamine receptor (DR) ligands. BRS-3D is a shape similarity profile calculated by superimposing the objective compounds against 300 template ligands from sc-PDB. First, we constructed five subtype selectivity regression models between DR subtypes D1-D2, D1-D3, D2-D3, D2-D4, and D3-D4. The models' 10-fold cross-validation-squared correlation coefficient (Q² , for training sets) and determination coefficient (R² , for test sets) were in the range of 0.5-0.7 and 0.6-0.8, respectively. Then, four pair-wise (D1-D2, D2-D3, D2-D4, and D3-D4) and a multitype (D2, D3, and D4) classification models were developed with the prediction accuracies around or over 90% (for test sets). Lastly, we compared the performances of the models developed on BRS-3D and classical descriptors. The results showed that BRS-3D performed similarly to classical 2D descriptors and better than other 3D descriptors. Combining BRS-3D and 2D descriptors can further improve the prediction performance. These results confirmed the capacity of BRS-3D in the prediction of DR subtype-selective ligands.

Synthesis and evaluation of fluoro substituted pyridinylcarboxamides and their phenylazo analogues for potential dopamine D3 receptor PET imaging

A series of fluoro substituted pyridinylcarboxamides and their phenylazo analogues with high affinity and selectivity for the dopamine D3 receptor was synthesized by the use of 6-fluoropyridine-3-carbonyl chloride (1) and fluorophenylazocarboxylic ester (2). Several of these compounds (9a-e and 10a-h) have been evaluated in vitro, among which 9b, 10a, 10c and 10d proved to have at least single-digit nanomolar affinity for D3. They also exhibit considerable selectivity over the other dopamine receptor subtypes and noteworthy selectivity over the structurally related serotonin receptor subtypes 5-HT(1A) and 5-HT₂, offering potential radiotracers for positron emission tomography.

1,4-Disubstituted aromatic piperazines with high 5-HT2A/D2 selectivity: Quantitative structure-selectivity investigations, docking, synthesis and biological evaluation

Simultaneous targeting of dopamine D2 and 5-HT2A receptors for the treatment of schizophrenia is one key feature of typical and atypical antipsychotics. In most of the top-selling antipsychotic drugs like aripiprazole and risperidone, high affinity to both receptors can be attributed to the presence of 1,4-disubstituted aromatic piperazines or piperidines as primary receptor recognition elements. Taking advantage of our in-house library of phenylpiperazine-derived dopamine receptor ligands and experimental data, we established highly significant CoMFA and CoMSIA models for the prediction of 5-HT2A over D2 selectivity. Subsequently, the models were applied to identify the selective candidates 55-57 from our newly synthesized library of GPCR ligands comprising a pyrazolo[1,5-a]pyridine head group and a 1,2,3-triazole based linker unit. The test compound 57 showed subnanomolar a Ki value (0.64 nM) for 5-HT2A and more than 10- and 30-fold selectivity over the dopamine receptor isoforms D2S and D2L, respectively.

Beyond small-molecule SAR: using the dopamine D3 receptor crystal structure to guide drug design

The dopamine D3 receptor is a target of pharmacotherapeutic interest in a variety of neurological disorders including schizophrenia, restless leg syndrome, and drug addiction. The high protein sequence homology between the D3 and D2 receptors has posed a challenge to developing D3 receptor-selective ligands whose behavioral actions can be attributed to D3 receptor engagement, in vivo. However, through primarily small-molecule structure-activity relationship (SAR) studies, a variety of chemical scaffolds have been discovered over the past two decades that have resulted in several D3 receptor-selective ligands with high affinity and in vivo activity. Nevertheless, viable clinical candidates remain limited. The recent determination of the high-resolution crystal structure of the D3 receptor has invigorated structure-based drug design, providing refinements to the molecular dynamic models and testable predictions about receptor-ligand interactions. This chapter will highlight recent preclinical and clinical studies demonstrating potential utility of D3 receptor-selective ligands in the treatment of addiction. In addition, new structure-based rational drug design strategies for D3 receptor-selective ligands that complement traditional small-molecule SAR to improve the selectivity and directed efficacy profiles are examined.

Radioligands for the dopamine receptor subtypes

The actions of the predominant neurotransmitter in the brain, dopamine, are mediated by the postsynaptic dopamine receptors. The five dopamine receptor subtypes and their regulation have been associated with a large variety of psychiatric diseases. Therefore, positron emission tomography (PET) imaging studies using suitable and selective (18) F-labeled and (11) C-labeled dopamine receptor radioligands could provide valuable knowledge on the impact of receptor density on the pathogenesis and evolvement of neuropsychiatric and neurological diseases. This special issue subchapter provides a summary of the most important (18) F-labeled and (11) C-labeled radioligands for PET imaging of the dopamine receptor subtypes, their radiochemistry, and characteristics from in vitro and in vivo applications, considering not only the already established PET ligands but also the recently published preclinical work.

Synthesis and characterization of a novel series of agonist compounds as potential radiopharmaceuticals for imaging dopamine D₂/₃ receptors in their high-affinity state

Imaging of dopamine D2/3 receptors (D2/3R) can shed light on the nature of several neuropsychiatric disorders in which dysregulation of D2/3R signaling is involved. Agonist D2/3 tracers for PET/SPECT imaging are considered to be superior to antagonists because they are more sensitive to dopamine concentrations and may selectively label the high-affinity receptor state. Carbon-11-labeled D2/3R agonists have been developed, but these short-lived tracers can be used only in centers with a cyclotron. Here, we report the development of a series of novel D2R agonist compounds based on the 2-aminomethylchromane (AMC) scaffold that provides ample opportunities for the introduction of longer-lived [(18)F] or [(123)I]. Binding experiments showed that several AMC compounds have a high affinity and selectivity for D2/3R and act as agonists. Two fluorine-containing compounds were [(18)F]-labeled, and both displayed specific binding to striatal D2/3R in rat brain slices in vitro. These findings encourage further in vivo evaluations.

A two-step target binding and selectivity support vector machines approach for virtual screening of dopamine receptor subtype-selective ligands

Target selective drugs, such as dopamine receptor (DR) subtype selective ligands, are developed for enhanced therapeutics and reduced side effects. In silico methods have been explored for searching DR selective ligands, but encountered difficulties associated with high subtype similarity and ligand structural diversity. Machine learning methods have shown promising potential in searching target selective compounds. Their target selective capability can be further enhanced. In this work, we introduced a new two-step support vector machines target-binding and selectivity screening method for searching DR subtype-selective ligands, which was tested together with three previously-used machine learning methods for searching D1, D2, D3 and D4 selective ligands. It correctly identified 50.6%–88.0% of the 21–408 subtype selective and 71.7%–81.0% of the 39–147 multi-subtype ligands. Its subtype selective ligand identification rates are significantly better than, and its multi-subtype ligand identification rates are comparable to the best rates of the previously used methods. Our method produced low false-hit rates in screening 13.56 M PubChem, 168,016 MDDR and 657,736 ChEMBLdb compounds. Molecular features important for subtype selectivity were extracted by using the recursive feature elimination feature selection method. These features are consistent with literature-reported features. Our method showed similar performance in searching estrogen receptor subtype selective ligands. Our study demonstrated the usefulness of the two-step target binding and selectivity screening method in searching subtype selective ligands from large compound libraries.

Software and resources for computational medicinal chemistry

Computer-aided drug design plays a vital role in drug discovery and development and has become an indispensable tool in the pharmaceutical industry. Computational medicinal chemists can take advantage of all kinds of software and resources in the computer-aided drug design field for the purposes of discovering and optimizing biologically active compounds. This article reviews software and other resources related to computer-aided drug design approaches, putting particular emphasis on structure-based drug design, ligand-based drug design, chemical databases and chemoinformatics tools.

Recent advances in the search for D3- and D4-selective drugs: probes, models and candidates

Dopamine D(2)-like receptors (including D(2), D(3) and D(4)) belong to the 'rhodopsin-like' family of G protein-coupled receptors (GPCRs), which represent the largest group of targets for bioactive molecules. Due to their high sequence similarity, the design of subtype-selective ligands requires rational and effective strategies. The general formula of 1,4-disubstituted aromatic piperidines and piperazines (1,4-DAPs) was extracted from classical dopaminergic drugs. The biological properties of this compound family are encoded by an aromatic head group that controls intrinsic activity, an amine moiety and a lipophilic appendage. D(3)- and D(4)-selective molecular probes and drug candidates were generated from the general formula of 1,4-DAP. Formal structural rearrangement led to investigational drugs beyond the 1,4-DAP structure. The very recent publication of the X-ray crystal structure of D(3) should facilitate efficient discovery of unprecedented chemotypes. However, the development of D(3)-selective agonists, functionally selective ligands and the exploitation of homo- and heteromers remain challenging.

Subtype selectivity of dopamine receptor ligands: insights from structure and ligand-based methods

Subtype selective dopamine receptor ligands have long been sought after as therapeutic and/or imaging agents for the treatment and monitoring of neurologic disorders. We report herein on a combined structure- and ligand-based approach to explore the molecular mechanism of the subtype selectivity for a large class of D₂-like dopamine receptor ligands (163 ligands in total). Homology models were built for both human D(₂L) and D₃ receptors in complex with haloperidol. Other ligands, which included multiple examples of substituted phenylpiperazines, were aligned against the binding conformations of haloperidol, and three-dimensional quantitative structure activity relationship (3D-QSAR) analyses were carried out. The receptor models show that although D₂ and D₃ share highly similar folds and 3D conformations, the slight sequence differences at their extracellular loop regions result in the binding cavity in D₂ being comparably shallower than in D₃, which may explain why some larger ligands bind with greater affinity at D₃ compared to D₂ receptors. The QSAR models show excellent correlation and high predictive power even when evaluated by the most stringent criteria. They confirm that the origins of subtype selectivity for the ligands arise primarily due to differences in the contours of the two binding sites. The predictive models suggest that while both steric and electrostatic interactions contribute to the compounds' binding affinity, the major contribution arises from hydrophobic interactions, with hydrogen bonding conferring binding specificity. The current work provides clues for the development of more subtype selective dopamine receptor ligands. Furthermore, it demonstrates the possibility of being able to apply similar modeling methods to other subtypes or classes of receptors to study GPCR receptor-ligand interactions at a molecular level.

An overview on GPCRs and drug discovery: structure-based drug design and structural biology on GPCRs

G protein-coupled receptors (GPCRs) represent 50-60% of the current drug targets. There is no doubt that this family of membrane proteins plays a crucial role in drug discovery today. Classically, a number of drugs based on GPCRs have been developed for such different indications as cardiovascular, metabolic, neurodegenerative, psychiatric, and oncologic diseases. Owing to the restricted structural information on GPCRs, only limited exploration of structure-based drug design has been possible. Much effort has been dedicated to structural biology on GPCRs and very recently an X-ray structure of the beta2-adrenergic receptor was obtained. This breakthrough will certainly increase the efforts in structural biology on GPCRs and furthermore speed up and facilitate the drug discovery process.

18F-Labeled FAUC 346 and BP 897 derivatives as subtype-selective potential PET radioligands for the dopamine D3 receptor

Disturbances of neutrotransmission at the dopamine D3 receptor are related to several neuropsychiatric diseases and in particular to drug addiction. Herein, we report the computer-assisted prediction of D3 selectivities of new fluoroalkoxy-substituted receptor ligands by means of 3D-QSAR analysis. As close analogues of the D3-selective lead compound FAUC 346 and BP 879, the (19)F-substituted test compounds 4 a-d were synthesized and evaluated. In vitro investigation of their binding characteristics in transfected Chinese Hamster Ovary (CHO) cells led to excellent K(i) values between 0.12 and 0.69 nM at the dopamine D3 subtype. The benzothiophene-substituted carboxamide 4 a (K(i)=0.12 nM) displayed 133 and 283-fold selectivity over the structurally related D2(Long) and D4 subtypes, respectively. Mitogenesis assays showed the behavior of partial agonists. Based on these data, we synthesized the [(18)F]fluoroethoxy-substituted radioligands [(18)F]4 a-d. The N-[4-[4-(2-hydroxyphenyl)piperazin-1-yl]butyl]-2-carboxamides 3 a-d were prepared and labeled with 2-[(18)F]fluoroethyltosylate in a two-step procedure. Optimization of the (18)F-labeling conditions led to radiochemical yields between 24 and 65 %.

A convenient preparation of 5-iodo-1,4-disubstituted-1,2,3-triazole: multicomponent one-pot reaction of azide and alkyne mediated by CuI-NBS

The system of CuI and NBS was found to provide both I (+) and Cu (+) for the first time. An efficient method for preparation of 5-iodo-1,4-disubstituted-1,2,3-triazole was achieved by multicomponent one-pot reaction of azides with alkynes in the presence of the novel CuI and NBS catalytic system. The high tolerance of various sensitive groups revealed the potential applications of this method in organic synthesis and drug discovery.

Click chemistry based solid phase supported synthesis of dopaminergic phenylacetylenes

'Click resins' enable solid phase supported reactions to work under nearly perfect conditions fulfilling the requirements of click chemistry. Utilizing the formylpyrrolylmethyltriazole (FPMT) linker 6, which is readily available via copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC), a BAL strategy could be successfully applied for a parallel synthesis of dopaminergic phenylacetylens. A focused library of 20 test compounds revealing three points of diversity was generated by a four-step SPOS approach including microwave assisted Sonogashira coupling. GPCR-ligand binding assays indicated excellent dopamine D3 and D4 receptor binding affinities which were identified to cause a partial agonist activity for the most potent test compounds 2c,e,i,k.

Heterocyclic Analogues of N-(4-(4-(2,3-Dichlorophenyl)piperazin-1-yl)butyl)arylcarboxamides with Functionalized Linking Chains as Novel Dopamine D3 Receptor Ligands: Potential Substance Abuse Therapeutic Agents

Dopamine D3 receptor antagonists and partial agonists have been shown to modulate drug-seeking effects induced by cocaine and other abused substances. Compound 6 [PG01037, (N-(4-(4-(2,3-dichlorophenyl)piperazin-1-yl)-trans-but-2-enyl)-4-pyridine-2-ylbenzamide)] and related analogues are currently being evaluated in animal models of drug addiction. In these studies, a discrepancy between in vitro binding affinity, in vivo occupancy, and behavioral potency has been observed. The purpose of this study was to examine (1) modifications of the 2-pyridylphenyl moiety of 6 and (2) hydroxyl, acetyl, and cyclopropyl substitutions on the butylamide linking chain systematically coupled with 2-fluorenylamide or 2-pyridylphenylamide and 2-methoxy- or 2,3-dichloro-substituted phenylpiperazines to measure the impact on binding affinity, D2/D3 selectivity, lipophilicity, and function. In general, these modifications were well tolerated at the human dopamine D3 (hD3) receptor (Ki = 1-5 nM) as measured in competition binding assays. Several analogues showed >100-fold selectivity for dopamine D3 over D2 and D4 receptors. In addition, while all the derivatives with an olefinic linker were antagonists, in quinpirole-stimulated mitogenesis at hD3 receptors, several of the hydroxybutyl-linked analogues (16, 17, 21) showed partial agonist activity. Finally, several structural modifications reduced lipophilicities while retaining the desired binding profile.