Molecular dynamics simulations reveal the mechanism of the interactions between the inhibitors and SIRT2 at atom level

ABSTRACT

The sirtuins are members of the histone deacetylase family of proteins that participate in a variety of cellular functions and play a close role in cancers. Exploring the proper inhibitors for SIRT2 has attracted great interest in the experiment. However, the detail of the interaction mechanisms between inhibitors and SIRT2 is not well understood. In our study, we synthesised SIRT2 selective inhibitor TPN0_C7 as a model of the proper inhibitor of SIRT2. With the molecular dynamics (MD) simulations, we found that the hydrophobic interactions play the important roles between the inhibitors and SIRT2. According to the conformation character of the inhibitor TPN0_C7, we also explored the natural product, Ge Gen (Puerarol is one of the components.), which is a very effective herb for cancer described in Traditional Chinese Medicine (TCMs) library. Dramatically, we found that the structurally similar inhibitors, Puerarol and TPN0_C7, have the similar binding sites on SIRT2. The hydrophobic and π-π interactions between inhibitors and SIRT2 are important during the progress of the dynamic simulations. In summary, our study uncovers the interaction mechanisms between the inhibitors and SIRT2 at atom level, which may provide clues to explore more proper inhibitors from TCMs.

KEYWORDS:

• SIRT2
• inhibitor
• molecular dynamics simulation
• TCMs
• hydrophobic and π–πinteractions

Acknowledgements

Huiyu Li thanks Prof. Guanghong Wei for giving the useful talk about this work. Qingjie Zhao thanks for the Support of the ‘Personalized Medicines – Molecular Signature-based Drug Discovery and Development’, Strategic Priority Research Program of the Chinese Academy of Sciences (grant number XDA12040322). Huiyu Li and Qingjie Zhao conceived and designed the study. Jingshan Shen and Qingjie Zhao provided experimental data. Xiaoyu Wang, Menghua Song and Shuang Zhao provided methodology. Xiaoyu Wang performed the computer simulations and dataanalysis. Xiaoyu Wang, Huiyu Li, Qingjie Zhao wrote the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by ‘Personalized Medicines – Molecular Signature-based Drug Discovery and Development’, Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDA12040322].