Exploring and Designing Potential Inhibitors of SIRT2 in Natural Products by Artificial Intelligence (AI) and Molecular Dynamics Methods

Abstract

Background:: The histone deacetylase family of proteins, which includes the sirtuins, participates in a wide range of cellular processes, and is intimately involved in neurodegenerative illnesses. The research on sirtuins has garnered a lot of interest. However, there are currently no effective therapeutic drugs. Methods:: In order to explore the potential inhibitors of SIRTs, we first screened four potential lead compounds of SIRT2 in Traditional Chinese Medicine (TCM) for nervous disease using the Auto- Dock Vina method. Then, with Molecular Dynamics (MD) simulation method, we discovered how these inhibitors from Traditional Chinese herbal medicines affect this protein at the atomic level. Results and Discussion:: We found hydrophobic interactions between inhibitors and SIRT2 to be crucial. The small molecules have been found to have strong effect on the residues in the zincbinding domain, exhibiting relationship with the signaling pathway. Finally, based on the conformational characteristics and the MD properties of the four potential inhibitors in TCM, we have designed the new skeleton molecules according to the parameters of binding energy, fingerprint similarity, 3D similarity, and RO5, with AI method using MolAICal software. Conclusion:: We have proposed the candidate inhibitor of SIRT2. Our research has provided a new approach that can be used to explore potential inhibitors from TCM. This could potentially pave the way for the creation of effective medicines.