SIRT2 inhibitors(University of Freiburg)

Selective inhibitors of sirtuin-2 (SIRT2) are increasingly recognized as potential therapeutics for cancer and neurodegenerative diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identified as some of the most potent and selective SIRT2 inhibitors reported to date (​Ai et al., 2016​; ​Ai et al., 2023​, ​Baroni et al., 2007​). In this study, a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model was developed using a dataset of 86 nicotinamide-based SIRT2 inhibitors from the literature, along with GRIND-derived pharmacophore models for selected inhibitors. External validation parameters emphasized the reliability of the 3D-QSAR model in predicting SIRT2 inhibition within the defined applicability domain. The interpretation of the 3D-QSAR model facilitated the generation of GRIND-derived pharmacophore models, which in turn enabled the design of novel SIRT2 inhibitors. Furthermore, based on molecular docking results for the SIRT1-3 isoforms, two classification models were developed: a SIRT1/2 model using the Naive Bayes algorithm and a SIRT2/3 model using the k-nearest neighbors algorithm, to predict the selectivity of inhibitors for SIRT1/2 and SIRT2/3. External validation parameters of the selectivity models confirmed their predictive power. Ultimately, the integration of 3D-QSAR, selectivity models and prediction of ADMET properties facilitated the identification of the most promising selective SIRT2 inhibitors for further development.

Sirtuins belong to a specific class of enzymes called NAD⁺-dependent protein deacetylases. Among them, SIRT2 is predominantly localized in the cytoplasm and plays a vital role in tumor development and progression. As a result, it becomes an important target for the development of anticancer drugs. While SIRT2 inhibitors have shown broad-spectrum cytotoxicity against various cancer cells, their ability to inhibit the growth of certain cancers like prostate cancer has been limited, possibly due to insufficient targeting properties. To overcome this limitation, our goal was to target prostate-specific membrane antigen (PSMA), a valuable biomarker for prostate cancer, using lysine-urea-glutamic acid (KUE) as a PSMA ligand. This approach allowed us to systematically design new SIRT2 inhibitors. Evaluation showed that compound 17 exhibited superior inhibitory activity, improved targeting properties, and enhanced antiproliferative efficacy specifically in prostate cancer cells. These findings suggest a promising strategy for utilizing SIRT2 inhibitors in prostate cancer therapy.