Characterization of β3-adrenergic receptor: determination of pharmacophore and 3D QSAR model for β3 adrenergic receptor agonism

Rational design, synthesis, and pharmacological evaluation of a cohort of novel beta-adrenergic receptors ligands enables an assessment of structure-activity relationships

Biomedical applications of molecules that are able to modulate β-adrenergic signaling have become increasingly attractive over the last decade, revealing that β-adrenergic receptors (β-ARs) are key targets for a plethora of therapeutic interventions, including cancer. Despite successes in β-AR drug discovery, identification of β-AR ligands that are useful as selective chemical tools in pharmacological studies of the three β-AR subtypes, or lead compounds for drug development is still a highly challenging task. This is mainly due to the intrinsic plasticity of β-ARs as G protein-coupled receptors in conjunction with the requirement for functional receptor subtype selectivity, tissue specificity and minimal off-target effects. With the aim to provide insight into structure-activity relationships for the three β-AR subtypes, we have synthesized and obtained the pharmacological profile of a series of structurally diverse compounds (named MC) that were designed based on the aryloxy-propanolamine scaffold of SR59230A. Comparative analysis of their predicted binding mode within the active and inactive states of the receptors in combination with their pharmacological profile revealed key structural elements that control their activity as agonists or antagonists, in addition to clues about substituents that mediate selectivity for one receptor subtype over the others. We anticipate that these results will facilitate selective β-AR drug development efforts.

Pharmacophore-guided Virtual Screening to Identify New β3-Adrenergic Receptor Agonists

The β₃‐adrenergic receptor (β₃‐AR) is found in several tissues such as adipose tissue and urinary bladder. It is a therapeutic target because it plays a role in thermogenesis, lipolysis, and bladder relaxation. Two β₃‐AR agonists are used clinically: mirabegron 1 and vibegron 2, which are indicated for overactive bladder syndrome. However, these drugs show adverse effects, including increased blood pressure in mirabegron patients. Hence, new β₃‐AR agonists are needed as starting points for drug development. Previous pharmacophore modeling studies of the β₃‐AR did not involve experimental in vitro validation. Therefore, this study aimed to conduct prospective virtual screening and confirm the biological activity of virtual hits. Ligand‐based pharmacophore modeling was performed since no 3D structure of human β₃‐AR is yet available. A dataset consisting of β₃‐AR agonists was prepared to build and validate the pharmacophore models. The best model was employed for prospective virtual screening, followed by physicochemical property filtering and a docking evaluation. To confirm the activity of the virtual hits, an in vitro assay was conducted, measuring cAMP levels at the cloned β₃‐AR. Out of 35 tested compounds, 4 compounds were active in CHO−K1 cells expressing the human β₃‐AR, and 8 compounds were active in CHO−K1 cells expressing the mouse β₃‐AR.

Efficiency of Homology Modeling Assisted Molecular Docking in G-protein Coupled Receptors

BACKGROUND

Molecular docking is in regular practice to assess ligand affinity on a target protein crystal structure. In the absence of protein crystal structure, the homology modeling or comparative modeling is the best alternative to elucidate the relationship details between a ligand and protein at the molecular level. The development of accurate homology modeling (HM) and its integration with molecular docking (MD) is essential for successful, rational drug discovery.

OBJECTIVE

The G-protein coupled receptors (GPCRs) are attractive therapeutic targets due to their immense role in human pharmacology. The GPCRs are membrane-bound proteins with the complex constitution, and the understanding of their activation and inactivation mechanisms is quite challenging. Over the past decade, there has been a rapid expansion in the number of solved G-protein-coupled receptor (GPCR) crystal structures; however, the majority of the GPCR structures remain unsolved. In this context, HM guided MD has been widely used for structure-based drug design (SBDD) of GPCRs.

METHODS

The focus of this review is on the recent (i) developments on HM supported GPCR drug discovery in the absence of GPCR crystal structures and (ii) application of HM in understanding the ligand interactions at the binding site, virtual screening, determining receptor subtype selectivity and receptor behaviour in comparison with GPCR crystal structures.

RESULTS

The HM in GPCRs has been extremely challenging due to the scarcity in template structures. In such a scenario, it is difficult to get accurate HM that can facilitate understanding of the ligand-receptor interactions. This problem has been alleviated to some extent by developing refined HM based on incorporating active /inactive ligand information and inducing protein flexibility. In some cases, HM proteins were found to outscore crystal structures.

CONCLUSION

The developments in HM have been highly operative to gain insights about the ligand interaction at the binding site and receptor functioning at the molecular level. Thus, HM guided molecular docking may be useful for rational drug discovery for the GPCRs mediated diseases.

Pharmacophore modeling, 3D-QSAR and molecular docking studies of quinazolines and aminopyridines as selective inhibitors of inducible nitric oxide synthase

Pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies have been performed on a dataset of thirty-two quinazoline and aminopyridine derivatives to get an insight into the important structural features required for binding to inducible nitric oxide synthase (iNOS). A four-point CPH (Common Pharmacophore Hypothesis), AHPR.29, with a hydrogen bond acceptor, hydrophobic group, positively charged ionizable group and an aromatic ring, has been obtained as the best pharmacophore model. Satisfactory statistical parameters of correlation ([Formula: see text]) and cross-validated ([Formula: see text]) correlation coefficients, 0.9288 and 0.6353, respectively, show high robustness and good predictive ability of our selected model. The contour maps have been developed from this model and the analysis has provided an interpretable explanation of the effect that various features and substituents have on the potency and selectivity of inhibitors towards iNOS. Docking studies have also been performed in order to analyze the interactions between the enzyme and the inhibitors. Our proposed model can thus be further used for screening a large database of compounds and design new iNOS inhibitors.

Pharmacological and Nutritional Effects of Natural Coumarins and Their Structure-Activity Relationships

Coumarins are fused benzene and pyrone ring systems with a wide spectrum of bioactivities, including antitumor, anti-inflammation, antiviral, and antibacterial effects. In this paper, the current development of coumarin-based drugs is introduced, and their structure-activity relationship is discussed by reviewing the relevant literature published in the past 20 years. Coumarin molecules can be customized by the target site to prevent systemic side effects by virtue of structural modification. The ortho-phenolic hydroxyl on the benzene ring has remarkable antioxidant and antitumor activities. Coumarins with aryl groups at the C-4 position have good activities in anti-HIV, antitumor, anti-inflammation, and analgesia. C-3 phenylcoumarins have strong anti-HIV and antioxidant effects. Tetracycline pyranocoumarins can significantly inhibit HIV; osthol structural analogues have antimicrobial activity. Praeruptorin C and its derivatives play an important role in lowering blood pressure and dilating coronary arteries, and khellactone derivatives have significant inhibitory effects on AIDS, cancer, and cardiovascular diseases. It is concluded that the specific site on the core structure of coumarin exhibits one or more activities due to the electronic or steric effects of the substituents. This review is intended to be conducive to rational design and development of more active and less toxic agents with a coumarin scaffold.

Integration of Ligand and Structure Based Approaches for CSAR-2014

The prediction of binding poses and affinities is an area of active interest in computer-aided drug design (CADD). Given the documented limitations with either ligand or structure based approaches, we employed an integrated approach and developed a rapid protocol for binding mode and affinity predictions. This workflow was applied to the three protein targets of Community Structure-Activity Resource-2014 (CSAR-2014) exercise: Factor Xa (FXa), Spleen Tyrosine Kinase (SYK), and tRNA (guanine-N(1))-methyltransferase (TrmD). Our docking and scoring workflow incorporates compound clustering and ligand and protein structure based pharmacophore modeling, followed by local docking, minimization, and scoring. While the former part of the protocol ensures high-quality ligand alignments and mapping, the subsequent minimization and scoring provides the predicted binding modes and affinities. We made blind predictions of docking pose for 1, 5, and 14 ligands docked into 1, 2, and 12 crystal structures of FXa, SYK, and TrmD, respectively. The resulting 174 poses were compared with cocrystallized structures (1, 5, and 14 complexes) made available at the end of CSAR. Our predicted poses were related to the experimentally determined structures with a mean root-mean-square deviation value of 3.4 Å. Further, we were able to classify high and low affinity ligands with the area under the curve values of 0.47, 0.60, and 0.69 for FXa, SYK, and TrmD, respectively, indicating the validity of our approach in at least two of the three systems. Detailed critical analysis of the results and CSAR methodology ranking procedures suggested that a straightforward application of our workflow has limitations, as some of the performance measures do not reflect the actual utility of pose and affinity predictions in the biological context of individual systems.

Hierarchical virtual screening: identification of potential high-affinity and selective β(3)-adrenergic receptor agonists

The hierarchical virtual screening (HVS) study, consisting of pharmacophore modelling, docking and VS of the generated focussed virtual library, has been carried out to identify novel high-affinity and selective β(3)-adrenergic receptor (β-AR) agonists. The best pharmacophore model, comprising one H-bond donor, two hydrophobes, one positive ionizable and one negative ionizable feature, was developed based on a training set of 51 β(3)-AR agonists using the pharmacophore generation protocol implemented in Discovery Studio. The model was further validated with the test set, external set and ability of the pharmacophoric features to complement the active site amino acids of the homology modelled β(3)-AR developed using MODELLER software. The focussed virtual library was generated using the structure-based insights gained from our earlier reported comprehensive study focussing on the structural basis of β-AR subtype selectivity of representative agonists and antagonists. The HVS with the sequential use of the best pharmacophore model and homology modelled β(3)-AR in the screening of the generated focussed library has led to the identification of potential virtual leads as novel high-affinity and selective β(3)-AR agonists.

The tertiary amine nitrogen atom of piperazine sulfonamides as a novel determinant of potent and selective beta3-adrenoceptor agonists

Novel compounds were prepared in fair to good yields as human beta(3)-adrenoceptor (beta(3)-AR) agonists. In particular, aryloxypropanolamines 7 a-d (EC(50)=0.57-2.1 nM) and arylethanolamines 12 a,b,e (EC(50)=6.38-19.4 nM) were designed to explore the effects of modifications at the right-hand side of these molecules on their activity as beta(3)-AR agonists. Piperidine sulfonamides 15 a-c, e-g (EC(50)=6.1-36.2 nM) and piperazine sulfonamide derivatives 20-29 (EC(50)=1.79-49.3 nM) were examined as compounds bearing a non-aromatic linker on the right- and left-hand sides of the molecules. Some piperazine sulfonamides were found to be potent and selective beta(3)-AR agonists, even if the amine nitrogen atom is tertiary and not secondary, as is the case for all beta(3)-AR agonists reported so far. (S)-3-{4-{N-{4-{2-[2-Hydroxy-3-(4-hydroxyphenoxy)propylamino]ethyl}phenyl}sulfamoyl}phenoxy}propanoic acid (7 d; EC(50)=0.57 nM), (R)-N-{4-[2-(2-hydroxy-2-phenylethylamino)ethyl]phenyl}-4-(3-octylureido)benzenesulfonamide (12 e; EC(50)=6.38 nM), (R)-2-[1-(4-methoxyphenylsulfonyl)piperidin-4-ylamino]-1-phenylethanol (15 f; EC(50)=6.1 nM), and (S)-4-{2-hydroxy-3-[4-(4-methoxyphenylsulfonyl)piperazin-1-yl]propoxy}phenol (25; EC(50)=1.79 nM) were found to be the most potent beta(3)-AR agonists of the aryloxypropanolamine, arylethanolamine, piperidine sulfonamide, and piperazine sulfonamide classes, respectively. The two most potent compounds were identified as possible candidates for further development of beta(3)-AR agonists useful in the treatment of beta(3)-AR-mediated pathological conditions.

Comparative 3D QSAR study on β(1)-, β(2)-, and β(3)-adrenoceptor agonists

A quantitative structure–activity relationship study of tryptamine-based derivatives of β₁-, β₂-, and β₃-adrenoceptor agonists was conducted using comparative molecular field analysis (CoMFA). Correlation coefficients (cross-validated r²) of 0.578, 0.595, and 0.558 were obtained for the three subtypes, respectively, in three different CoMFA models. All three CoMFA models have different steric and electrostatic contributions, implying different requirements inside the binding cavity. The CoMFA coefficient contour plots of the three models and comparisons among these plots provide clues regarding the main chemical features responsible for the biological activity variations and also result in predictions which correlate very well with the observed biological activity. Based on the analysis, a summary regeospecific description of the requirements for improving β-adrenoceptor subtype selectivity is given.

Substituted 1,2,3,4-tetrahydroquinolin-6-yloxypropanes as beta3-adrenergic receptor agonists: design, synthesis, biological evaluation and pharmacophore modeling

In search of potent beta(3)-adrenergic receptor agonists, a series of novel substituted 1,2,3,4-tetrahydroquinolin-6-yloxypropanes has been synthesized and evaluated for their beta(3)-adrenergic receptor agonistic activity (ranging from -17.73% to 90.64% inhibition at 10 microM) using well established Human SK-N-MC neuroblastoma cells model. Four molecules viz. 11, 15, 22 and 23 showed beta(3)-AR agonistic IC(50) value of 0.55, 0.59, 1.18 and 1.76 microM, respectively. These four candidates have been identified as possible leads for further development of beta(3)-adrenergic receptor agonists for obesity and Type-II diabetes pharmacotherapy. The free OH and NH functions are found to be essential for beta(3)-adrenergic receptor agonistic activity. Among the synthesized beta(3)-adrenergic receptor agonists having 1,2,3,4-tetrahydroquinoline scaffold, the N-benzyl group is found to be superior over N-arylsulfonyl group. A putative pharmacophore model has been modeled considering the above four active molecules which distinguishes well between the active and inactive molecules.

Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads

Histone deacetylase is one of the important targets in the treatment of solid tumors and hematological cancers. A total of 20 well-defined inhibitors were used to generate Pharmacophore models using and HypoGen module of Catalyst. These 20 molecules broadly represent 3 different chemotypes. The best HypoGen model consists of four-pharmacophore features--one hydrogen bond acceptor, one hydrophobic aliphatic and two ring aromatic centers. This model was validated against 378 known HDAC inhibitors with a correlation of 0.897 as well as enrichment factor of 2.68 against a maximum value of 3. This model was further used to retrieve molecules from NCI database with 238,819 molecules. A total of 4638 molecules from a pool of 238,819 molecules were identified as hits while 297 molecules were indicated as highly active. Also, a Similarity analysis has been carried out for set of 4638 hits with respect to most active molecule of each chemotypes which validated not only the Virtual Screening potential of the model but also identified the possible new Chemotypes. This type of Similarity analysis would prove to be efficient not only for lead generation but also for lead optimization.

Antihyperglycemic and antidyslipidemic agent from Aegle marmelos

The plant Aegle marmelos belongs to the family of Rutaceae. From the leaves of A. marmelos an alkaloidal-amide, Aegeline 2, was isolated and found to have antihyperglycemic activity as evidenced by lowering the blood glucose levels by 12.9% and 16.9% at 5 and 24h, respectively, in sucrose challenged streptozotocin induced diabetic rats (STZ-S) model at the dose of 100mg/kg body weight. Aegeline 2 has also significantly decreased the plasma triglyceride (Tg) levels by 55% (P<0.001), total cholesterol (TC) by 24% (P<0.05), and free fatty acids (FFA) by 24%, accompanied with increase in HDL-C by 28% and HDL-C/TC ratio by 66% in dyslipidemic hamster model at the dose of 50mg/kg body weight. The reasonable mapping of compound 2 to validated pharmacophoric hypothesis and 3D QSAR model with an estimated activity (283nM) suggest that the compound 2 might be a beta(3)-AR agonist.