4.7 Article

Structural basis of fullerene derivatives as novel potent inhibitors of protein acetylcholinesterase without catalytic active site interaction: insight into the inhibitory mechanism through molecular modeling studies

期刊

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/07391102.2019.1576543

关键词

Acetylcholinesterase; inhibitor; fullerene derivative; molecular simulation

向作者/读者索取更多资源

Acetylcholinesterase (AChE) is an important kind of esterase that plays a key biological role in the central and peripheral nervous systems. Recent research has demonstrated that some fullerene derivatives serve as a new nanoscale class of potent inhibitors of AChE, but the specific inhibition mechanism remains unclear. In the present article, several molecular modeling methods, such as molecular docking, molecular dynamics simulations and molecular mechanics/generalized Born surface area calculations, were used for the investigation of the binding mode and inhibition mechanism of fullerene inhibitions for AChE. Results revealed that fullerene inhibitors block the entrance of substrates by binding with the peripheral anionic site (PAS) region. Thus, fullerene derivatives might mainly serve as competitive inhibitors. The interactions of a fullerene backbone with AChE are at the same level in different single side chain systems and seem to be related to the length or aromaticity of the side chain. The inhibitor with multihydroxyl side chains shows an obviously large electrostatic interaction as it forms additional hydrogen bonds with AChE. Moreover, fullerene derivatives might exhibit noncompetitive inhibition partly by affecting some secondary structures around them. Thus, the destructions of these secondary structures can lead to conformational changes in some important regions, such as the catalytic triad and acyl pocket. The investigation is of great importance to the discovery of good fullerene inhibitors. Communicated by Ramaswamy H. Sarma

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据