Marcus Malo

Chroman-4-one- and chromone-based sirtuin 2 inhibitors with antiproliferative properties in cancer cells.

Sirtuins (SIRTs) catalyze the NAD(+)-dependent deacetylation of N(ε)-acetyl lysines on various protein substrates. SIRTs are interesting drug targets as they are considered to be related to important pathologies such as inflammation and aging-associated diseases. We have previously shown that chroman-4-ones act as potent and selective inhibitors of SIRT2. Herein we report novel chroman-4-one and chromone-based SIRT2 inhibitors containing various heterofunctionalities to improve pharmacokinetic properties. The compounds retained both high SIRT2 selectivity and potent inhibitory activity. Two compounds were tested for their antiproliferative effects in breast cancer (MCF-7) and lung carcinoma (A549) cell lines. Both compounds showed antiproliferative effects correlating with their SIRT2 inhibition potency. They also increased the acetylation level of α-tubulin, indicating that SIRT2 is likely to be the target in cancer cells. A binding mode of the inhibitors that is consistent with the SAR data was proposed based on a homology model of SIRT2.

Selective Pharmacophore Models of Dopamine D1 and D2 Full Agonists Based on Extended Pharmacophore Features

This study is focused on the identification of structural features that determine the selectivity of dopamine receptor agonists toward D1 and D2 receptors. Selective pharmacophore models were developed for both receptors. The models were built by using projected pharmacophoric features that represent the main agonist interaction sites in the receptor (the Ser residues in TM5 and the Asp in TM3), a directional aromatic feature in the ligand, a feature with large positional tolerance representing the positively charged nitrogen in the ligand, and sets of excluded volumes reflecting the shapes of the receptors. The sets of D1 and D2 ligands used for modeling were carefully selected from published sources and consist of structurally diverse, conformationally rigid full agonists as active ligands together with structurally related inactives. The robustness of the models in discriminating actives from inactives was tested against four ensembles of conformations generated by using different established methods and different force fields. The reasons for the selectivity can be attributed to both geometrical differences in the arrangement of the features, e.g., different tilt angels of the π system, as well as shape differences covered by the different sets of excluded volumes. This work provides useful information for the design of new D1 and D2 agonists and also for comparative homology modeling of D1 and D2 receptors. The approach is general and could therefore be applied to other ligand–protein interactions for which no experimental protein structure is available.

Investigation of D1 Receptor–Agonist Interactions and D1/D2 Agonist Selectivity Using a Combination of Pharmacophore and Receptor Homology Modeling

The aim of this study was to use a combined structure and pharmacophore modeling approach to extract information regarding dopamine D1 receptor agonism and D1/D2 agonist selectivity. A 3D structure model of the D1 receptor in its agonist‐bound state was constructed with a full D1 agonist present in the binding site. Two different binding modes were identified using (+)‐doxanthrine or SKF89626 in the modeling procedure. The 3D model was further compared with a selective D1 agonist pharmacophore model. The pharmacophore feature arrangement was found to be in good agreement with the binding site composition of the receptor model, but the excluded volumes did not fully reflect the shape of the agonist binding pocket. A new receptor‐based pharmacophore model was developed with forbidden volumes centered on atom positions of amino acids in the binding site. The new pharmacophore model showed a similar ability to discriminate as the previous model. A comparison of the 3D structures and pharmacophore models of D1 and D2 receptors revealed differences in shape and ligand‐interacting features that determine selectivity of D1 and D2 receptor agonists. A hydrogen bond pharmacophoric feature (Ser‐TM5) was shown to contribute most to the selectivity. Non‐conserved residues in the binding pocket that strongly contribute to D1/D2 receptor agonist selectivity were also identified; those were Ser/Cys3.36, Tyr/Phe5.38, Ser/Tyr5.41, and Asn/His6.55 in the transmembrane (TM) helix region, together with Ser/Ile and Leu/Asn in the second extracellular loop (EC2). This work provides useful information for the design of new selective D1 and D2 agonists. The combined receptor structure and pharmacophore modeling approach is considered to be general, and could therefore be applied to other ligand–protein interactions for which experimental information is limited.

Behavioral Analysis of Dopaminergic Activation in Zebrafish and Rats Reveals Similar Phenotypes

Zebrafish is emerging as a complement to mammals in behavioral studies; however, there is a lack of comparative studies with rodents and humans to establish the zebrafish as a predictive translational model. Here we present a detailed phenotype evaluation of zebrafish larvae, measuring 300-3000 variables and analyzing them using multivariate analysis to identify the most important ones for further evaluations. The dopamine agonist apomorphine has previously been shown to have a complex U-shaped dose-response relationship in the variable distance traveled. In this study, we focused on breaking down distance traveled into more detailed behavioral phenotypes for both zebrafish and rats and identified in the multivariate analysis low and high dose phenotypes with characteristic behavioral features. Further analysis of single parameters also identified an increased activity at the lowest concentration indicative of a U-shaped dose-response. Apomorphine increased the distance of each swim movement (bout) at both high and low doses, but the underlying behavior of this increase is different; at high dose, both bout duration and frequency increased whereas bout max speed was higher at low dose. Larvae also displayed differences in place preference. The low dose phenotype spent more time in the center, indicative of an anxiolytic effect, while the high-dose phenotype had a wall preference. These dose-dependent effects corroborated findings in a parallel rat study and previous observations in humans. The translational value of pharmacological zebrafish studies was further evaluated by comparing the amino acid sequence of the dopamine receptors (D1-D4), between zebrafish, rats and humans. Humans and zebrafish share 100% of the amino acids in the binding site for D1 and D3 whereas D2 and D4 receptors share 85-95%. Molecular modeling of dopamine D2 and D4 receptors indicated that nonconserved amino acids have limited influence on important ligand-receptor interactions.

Investigation of D2 Receptor–Agonist Interactions Using a Combination of Pharmacophore and Receptor Homology Modeling

A combined modeling approach was used to identify structural factors that underlie the structure–activity relationships (SARs) of full dopamine D2 receptor agonists and structurally similar inactive compounds. A 3D structural model of the dopamine D2 receptor was constructed, with the agonist (−)‐(R)‐2‐OH‐NPA present in the binding site during the modeling procedure. The 3D model was evaluated and compared with our previously published D2 agonist pharmacophore model. The comparison revealed an inconsistency between the projected hydrogen bonding feature (Ser‐TM5) in the pharmacophore model and the TM5 region in the structure model. A new refined pharmacophore model was developed, guided by the shape of the binding site in the receptor model and with less emphasis on TM5 interactions. The combination of receptor and pharmacophore modeling also identified the importance of His3936.55 for agonist binding. This convergent 3D pharmacophore and protein structure modeling strategy is considered to be general and can be highly useful in less well‐characterized systems to explore ligand–receptor interactions. The strategy has the potential to identify weaknesses in the individual models and thereby provides an opportunity to improve the discriminating predictivity of both pharmacophore searches and structure‐based virtual screens.

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β1 adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D2 receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D2 receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.

Chiral Dihydrobenzofuran Acids Show Potent Retinoid X Receptor–Nuclear Receptor Related 1 Protein Dimer Activation

The nuclear receptor Nurr1 can be activated by RXR via heterodimerization (RXR-Nurr1) and is a promising target for treating neurodegenerative diseases. We herein report the enantioselective synthesis and SAR of sterically constricted benzofurans at RXR. The established SAR, using whole cell functional assays, lead to the full agonist 9a at RXR (pEC50 of 8.2) and RXR-Nurr1. The X-ray structure shows enantiomeric discrimination where 9a optimally addresses the ligand binding pocket of RXR.