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.

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.

Photoaffinity labeling (PAL) was used to identify the binding site of chroman-4-one-based SIRT2-selective inhibitors. The photoactive diazirine 4, a potent SIRT2 inhibitor, was subjected to detailed photochemical characterization. In PAL experiments with SIRT2, a tryptic peptide originating from the covalent attachment of photoactivated 4 was identified. The peptide covers both the active site of SIRT2 and the proposed binding site of chroman-4-one-based inhibitors. A high-power LED was used as source for the monochromatic UV light enabling rapid photoactivation.

This study is focused on the identification of structural features that determine the selectivity of dopamine receptor agonists toward D(1) and D(2) 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 D(1) and D(2) 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 pi system, as well as shape differences covered by the different sets of excluded volumes. This work provides useful information for the design of new D(1) and D(2) agonists and also for comparative homology modeling of D(1) and D(2) receptors. The approach is general and could therefore be applied to other ligand-protein interactions for which no experimental protein structure is available.

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.