SIRT2 inhibitors(University of Freiburg)

We aimed to conduct in silico screening of the potential phytoconstituent from a natural product database to find SIRT2 inhibitors.

Alzheimer's disease (AD) is the most prevalent type of dementia, characterized by behavioral and mental symptoms as well as a progressive loss of cognitive ability. Since SIRT2 may be detrimental to neurological illnesses, it is a prime target for research into SIRT2 inhibitors.

To identify the SIRT2 inhibitors and their role in AD.

We have utilized NPAtlas database and screened using pharmacophore-based virtual screening, molecular docking, and simulation. The Natural Products Atlas provides unrestricted access to various natural products derived from bacteria and fungi, allowing researchers to investigate and visualize the extensive chemical diversity in the natural world.

From in silico screening data, we have found phytoconstituents that could function as SIRT2 inhibitors. Six phytoconstituents were identified using pharmacophore-based virtual screening. According to molecular docking, Kurasoin B outperformed the reference molecule regarding binding energy. Kurasoin B exhibited a binding affinity of -12.543 kcal/mol, whereas the binding affinity of the reference molecule was -12.089 kcal/mol. The Kurasoin B complex with SIRT2 was determined to be stable throughout the simulation by performing MD simulation, with an RMSD of 2.88 (Å), whereas the reference and free protein displayed RMSDs of 3.74 and 4.70 (Å), respectively.

In silico studies and data analysis, suggest that Kurasoin B may be able to suppress the SIRT2 protein for managing AD.

The search and development of effective sirtuin small molecule inhibitors (SIRTIs) continues to draw great attention due to their wide range of pharmacological applications. Based on SIRTs' involvement in different biological pathways, their ligands were investigated for many diseases, such as cancer, neurodegenerative disorders, diabetes, cardiovascular diseases and autoimmune diseases. The elucidation of a substantial number of SIRT2-ligand complexes is steering the identification of novel and more selective modulators. Among them, SIRT2 in the presence of the SirReal2 analog series was the most studied. On this basis, we recently reported structure-based analyses leading to the discovery of thiazole-based compounds acting as SIRT2 inhibitors (T1, SIRT2 IC₅₀ = 17.3 µM). Herein, ligand-based approaches followed by molecular docking simulations allowed us to evaluate in silico a novel small series of thiazoles (3a-3d and 5a, 5d) as putative SIRT2 inhibitors. Results from the computational studies revealed comparable molecular interaction fields (MIFs) and docking positionings of most of these compounds with respect to reference SIRT2Is. Biochemical and biological assays validated this study and pointed to compound 5a (SIRT2 IC₅₀ = 9.0 µM) as the most interesting SIRT2I that was worthy of further development as an anticancer agent.