Derivation of Self-inhibitory Helical Peptides to Target Rho-kinase Dimerization in Cerebrovascular Malformation: Structural Bioinformatics Analysis and Peptide Binding Assay

详细信息    查看全文

• 作者：Xuyang Wang ; Dianqi Hou ; Weiwei Dai ; Wenwei Gao ; Shiming Ju ; Heli Cao ; Lin Zhang ; Gan Wang ; Yan Guo ; Shiwen Chen ; Hengli Tian and Zhiqiang Li
• 刊名：Molecular Informatics
• 出版年：2016
• 出版时间：July 2016
• 年：2016
• 卷：35
• 期：6-7
• 页码：262-267
• 全文大小：1650K
• ISSN：1868-1751

文摘

Rho-kinase dimerization is essential for its kinase activity and biological function; disruption of the dimerization has recently been established as a new and promising therapeutics strategy for cerebrovascular malformation (CM). Based on Rho-kinase dimer crystal structure we herein combined in silico analysis and in vitro assay to rationally derive self-inhibitory peptides from the dimerization interface. Three peptides namely Hlp1, Hlp2 and Hlp3 were successfully designed that have potential capability to rebind at the dimerization domain of Rho-kinase. Molecular dynamics (MD) simulations revealed that these peptides are helically structured when bound to Rho-kinase, but exhibit partially intrinsic disorder in unbound state. Binding free energy (BFE) analysis suggested that the peptides have a satisfactory energetic profile to interact with Rho-kinase. The computational findings were then substantiated by fluorescence anisotropy assays, conforming that the helical peptides can bind tightly to Rho-kinase with affinity K_D at micromolar level. These designed peptides are considered as lead molecular entities that can be further modified and optimized to obtain more potent peptidomimetics as self-competitors to disrupt Rho-kinase dimerization in CM.