Development of a NanoBRET assay to validate inhibitors of Sirt2-mediated lysine deacetylation and defatty-acylation that block prostate cancer cell migration.

Sirtuin2 (Sirt2) with its NAD+-dependent deacetylase and defatty-acylase activities plays a central role in the regulation of specific cellular functions. Dysregulation of Sirt2 activity has been associated with the pathogenesis of many diseases, thus making Sirt2 a promising target for pharmaceutical intervention. Herein, we present new high affinity Sirt2 selective Sirtuin-Rearranging Ligands (SirReals) that inhibit both Sirt2-dependent deacetylation and defatty-acylation in vitro and in cells. We show that simultaneous inhibition of both Sirt2 activities results in strongly reduced levels of the oncoprotein c-Myc and an inhibition of cancer cell migration. Furthermore, we describe the development of a NanoBRET-based assay for Sirt2, thereby providing a method to study cellular target engagement for Sirt2 in a straightforward and accurately quantifiable manner. Applying this assay, we could confirm cellular Sirt2 binding of our new Sirt2 inhibitors and correlate their anticancer effects with their cellular target engagement.

Photochromic histone deacetylase inhibitors based on dithienylethenes and fulgimides.

Histone deacetylases (HDACs) play a crucial role in numerous biological processes and therefore are targeted in anticancer research and in the field of epigenetics. Dithienylethenes (DTEs) and fulgimides were functionalized with hydroxamic acids, which is a known moiety binding to zinc dependent HDACs, to gain photoswitchable HDAC inhibitors. The new DTE based inhibitors showed moderate photochromic properties in polar solvents and the inhibitory activity changes up to a factor of four. The photochromic performance of the prepared fulgimide inhibitors was very good, even in aqueous buffer. They achieved a maximum three-fold difference in inhibitory activity. Docking experiments using the crystal structures of the tested enzymes gave a rationale for the observed moderate differences in the activities of the inhibitors.

Histone acetyltransferase inhibitors block neuroblastoma cell growth in vivo.

We have previously described novel histone acetyltransferase (HAT) inhibitors that block neuroblastoma cell growth in vitro. Here we show that two selected pyridoisothiazolone HAT inhibitors, PU139 and PU141, induce cellular histone hypoacetylation and inhibit growth of several neoplastic cell lines originating from different tissues. Broader in vitro selectivity profiling shows that PU139 blocks the HATs Gcn5, p300/CBP-associated factor (PCAF), CREB (cAMP response element-binding) protein (CBP) and p300, whereas PU141 is selective toward CBP and p300. The pan-inhibitor PU139 triggers caspase-independent cell death in cell culture. Both inhibitors block growth of SK-N-SH neuroblastoma xenografts in mice and the PU139 was shown to synergize with doxorubicin in vivo. The latter also reduces histone lysine acetylation in vivo at concentrations that block neoplastic xenograft growth. This is one of the very few reports on hypoacetylating agents with in vivo anticancer activity.

Receptor-based 3D QSAR analysis of estrogen receptor ligands--merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods.

One of the major challenges in computational approaches to drug design is the accurate prediction of binding affinity of biomolecules. In the present study several prediction methods for a published set of estrogen receptor ligands are investigated and compared. The binding modes of 30 ligands were determined using the docking program AutoDock and were compared with available X-ray structures of estrogen receptor-ligand complexes. On the basis of the docking results an interaction energy-based model, which uses the information of the whole ligand-receptor complex, was generated. Several parameters were modified in order to analyze their influence onto the correlation between binding affinities and calculated ligand-receptor interaction energies. The highest correlation coefficient (r2 = 0.617, q2Loo = 0.570) was obtained considering protein flexibility during the interaction energy evaluation. The second prediction method uses a combination of receptor-based and 3D quantitative structure-activity relationships (3D QSAR) methods. The ligand alignment obtained from the docking simulations was taken as basis for a comparative field analysis applying the GRID/GOLPE program. Using the interaction field derived with a water probe and applying the smart region definition (SRD) variable selection, a significant and robust model was obtained (r2 = 0.991, q2LOO = 0.921). The predictive ability of the established model was further evaluated by using a test set of six additional compounds. The comparison with the generated interaction energy-based model and with a traditional CoMFA model obtained using a ligand-based alignment (r2 = 0.951, q2L00 = 0.796) indicates that the combination of receptor-based and 3D QSAR methods is able to improve the quality of the underlying model.