β-环糊精与客体分子结合模式研究

1.项目说明

研究主题分子β-环糊精(β-CD)与客体分子cinnarizine的结合模式、相互作用力和结合位点。

图1 cinnarizine
图1 cinnarizine

2.计算方法

从Crystallography Open Database(http://www.crystallography.net/)下载β-环糊精(COD 编号:2100207[1]),采用ChemBioDraw 画出客体的化学结构。

采用UCSF Chimera[3]处理主客体结构,去除β-CD晶体结构中的冗余原子,得到β-CD和客体分子的三维结构。对于主客体结构均采用Dock Prep模块添加氢原子,分别添加AMBER14SB 力场和AM1-BCC 电荷[4, 5],然后对主客体结构分别进行能量优化。采用Chimera 中的DMS工具以半径为1.4Å 的探针生成主体分子的表面,使用sphgen 模块生成填充在空腔中的球状集合(Spheres),使用Grid 模块生成Grid 文件,该文件用于快速的基于Grid 的能量打分评价。采用DOCK6.7 程序[6, 7]进行柔性对接(flexible docking),生成1000个不同的构象取向(orientation)以及获得客体与主体的静电和范德华相互作用,并由此计算得到Grid 打分。通过聚类分析(RMSD 阈值2.0Å),得到打分最佳的构象。

3.结果分析

A.结合构象打分

采用DOCK6.7程序预测主客体的结合模式,获得初步的结合构象,打分情况如下(表1)。目视检查β-CD与Cinnarizine的结合模式有2种,且主客体之间的静电力为零。

表1.主客体的对接打分

Host Guest Pose Grid Score Grid_vdw Grid_es Int_energy
β-CD Cinnarizine 1 -42.095184 -42.095184 0 11.869987
2 -39.931282 -39.931282 0 9.265942
3 -39.879784 -39.879784 0 8.421596
4 -38.744133 -38.744133 0 9.59088

 

B.结合模式分析:β-环糊精(β-CD)与客体Cinnarizine

图2显示了主体β-CD与客体Cinnarizine结合的DOCK6.7对接结果,目视检查发现主客体之间有2种结合模式。客体分子Cinnarizine包埋于主体β-CD 内腔中,主客体之间无氢键相互作用,两者主要靠疏水作用维持结合。

图2 主体β-CD与客体Cinnarizine的结合模式
图2 主体β-CD与客体Cinnarizine的结合模式

参考文献

[1] Tsorteki Frantzeska, Bethanis Kostas, Pinotsis Nikos, Giastas Petros, and Mentzafos Dimitris. Inclusion compounds of plant growth regulators in cyclodextrins. v. 4-chlorophenoxyacetic acid encapsulated in beta-cyclodextrin and heptakis(2,3,6-tri-o-methyl)-beta-cyclodextrin. Acta Crystallographica Section B, 61(2):207–217, 2005.
[2] Yong Yao, Min Xue, Jianzhuang Chen, Mingming Zhang, and Feihe Huang. An amphiphilic pillar[5]arene: Synthesis, controllable self-assembly in water, and application in calcein release and tnt adsorption. Journal of the American Chemical Society, 134:15712–15715, 2012.
[3] Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, MengEC, and Ferrin TE. Ucsf chimera–a visualization system for exploratory research and analysis. J Comput Chem, 25(13):1605–12, 2004.
[4] Araz Jakalian, Bruce L. Bush, David B. Jack, and Christopher I. Bayly. Fast, efficient generation of high-quality atomic charges. am1-bcc model: I. method. Journal of Computational Chemistry, 21(2):132–146, January 2000.
[5] Araz Jakalian, David B. Jack, and Christopher I. Bayly. Fast, efficient generation of high-quality atomic charges. am1-bcc model: I. parameterization and validation. Journal of Computational Chemistry, 23(16):1623–1641, December 2002.
[6] P. Therese Lang, Scott R. Brozell, Sudipto Mukherjee, Eric F. Pettersen, Elaine C. Meng, Veena Thomas, Robert C. Rizzo, David A. Case, Thomas L. James James, and Irwin D. Kuntz. Dock 6: Combining techniques to model rna-small molecule complexes. RNA, 5(6):1–12, December 2009.
[7] Sudipto Mukherjee, Trent E. Balius, and Robert C. Rizzo. Docking validation resources: Protein family and ligand flexibility experiments. Journal of Chemical Information and Modeling, 50(11):1986–2000, October 2010.
X