• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于氨基酸残基出现统计的蛋白质结构域边界预测

[Prediction of protein domain boundaries based on statistics of appearance of amino acid residues].

作者信息

Galzitskaia O V, Dovidchenko N V, Lobanov M Iu, Garbuzinskiĭ S A

出版信息

Mol Biol (Mosk). 2006 Jan-Feb;40(1):111-21.

PMID:16523698
Abstract

We have created a database of two-domain proteins with homology less than 25% (452 proteins). Based on one half of this set of proteins statistics of appearance of amino acid residues on the domain boundaries of multiple domain proteins has been obtained. Small and hydrophilic amino acids (proline, glycine, asparagine, glutamic acid, arginine and others) appear on the domain boundaries more often than in the whole protein. Opposite, hydrophobic amino acid residues (tryptophane, methionine, phenylalanine and others) appear on the domain boundaries more rarely. The obtained scales of the appearance of amino acid residues on the boundary regions from the statistics have been used for calculation of domain boundaries in the proteins of the second half of the database. The probability scale obtained by averaging the appearance of amino acid residues on the domain boundary region including 8 residues (+/-4 residues from the real domain boundary) gives the best result: for 57% of proteins the predicted boundary was closer than 40 residues to the boundary assigned from three-dimensional structures, for 41% it was closer than 20 residues from the real boundary. The probability scale was used to predict domain boundaries for proteins with unknown three-dimensional structure (international competition CASP6).

摘要

我们创建了一个由同源性低于25%的双结构域蛋白质组成的数据库(452种蛋白质)。基于这组蛋白质中的一半,我们获得了多结构域蛋白质结构域边界上氨基酸残基出现情况的统计数据。与整个蛋白质相比,小的亲水性氨基酸(脯氨酸、甘氨酸、天冬酰胺、谷氨酸、精氨酸等)在结构域边界上出现的频率更高。相反,疏水性氨基酸残基(色氨酸、甲硫氨酸、苯丙氨酸等)在结构域边界上出现的频率更低。根据统计数据得到的氨基酸残基在边界区域出现的比例,已被用于计算数据库后半部分蛋白质中的结构域边界。通过对包括8个残基(从实际结构域边界起±4个残基)的结构域边界区域上氨基酸残基出现情况进行平均得到的概率比例给出了最佳结果:对于57%的蛋白质,预测边界与从三维结构确定的边界的距离小于40个残基,对于41%的蛋白质,预测边界与实际边界的距离小于20个残基。该概率比例被用于预测三维结构未知的蛋白质的结构域边界(国际蛋白质结构预测竞赛CASP6)。

相似文献

1
[Prediction of protein domain boundaries based on statistics of appearance of amino acid residues].基于氨基酸残基出现统计的蛋白质结构域边界预测
Mol Biol (Mosk). 2006 Jan-Feb;40(1):111-21.
2
Armadillo: domain boundary prediction by amino acid composition.犰狳:基于氨基酸组成的结构域边界预测
J Mol Biol. 2005 Jul 29;350(5):1061-73. doi: 10.1016/j.jmb.2005.05.037.
3
Domain boundary prediction based on profile domain linker propensity index.基于序列轮廓结构域连接子倾向指数的结构域边界预测
Comput Biol Chem. 2006 Apr;30(2):127-33. doi: 10.1016/j.compbiolchem.2006.01.001. Epub 2006 Mar 13.
4
SnapDRAGON: a method to delineate protein structural domains from sequence data.SnapDRAGON:一种从序列数据中描绘蛋白质结构域的方法。
J Mol Biol. 2002 Feb 22;316(3):839-51. doi: 10.1006/jmbi.2001.5387.
5
Prediction of protein domain boundaries from sequence alone.仅从序列预测蛋白质结构域边界。
Protein Sci. 2003 Apr;12(4):696-701. doi: 10.1110/ps.0233103.
6
DomNet: protein domain boundary prediction using enhanced general regression network and new profiles.DomNet:使用增强型通用回归网络和新轮廓进行蛋白质结构域边界预测
IEEE Trans Nanobioscience. 2008 Jun;7(2):172-81. doi: 10.1109/TNB.2008.2000747.
7
Use of variable selection in modeling the secondary structural content of proteins from their composition of amino acid residues.在根据氨基酸残基组成对蛋白质二级结构含量进行建模时使用变量选择。
J Chem Inf Comput Sci. 2004 Jan-Feb;44(1):113-21. doi: 10.1021/ci034037p.
8
Protein structure prediction based on sequence similarity.基于序列相似性的蛋白质结构预测。
Methods Mol Biol. 2009;569:129-56. doi: 10.1007/978-1-59745-524-4_7.
9
Improvement of domain linker prediction by incorporating loop-length-dependent characteristics.通过纳入环长度依赖性特征改进结构域连接子预测。
Biopolymers. 2006;84(2):161-8. doi: 10.1002/bip.20361.
10
Sequence-based protein domain boundary prediction using BP neural network with various property profiles.基于序列的蛋白质结构域边界预测:使用具有各种属性概况的BP神经网络
Proteins. 2008 Apr;71(1):300-7. doi: 10.1002/prot.21745.

引用本文的文献

1
PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.PDP-CON:使用共识方法预测蛋白质序列中的结构域/连接子残基。
J Mol Model. 2016 Apr;22(4):72. doi: 10.1007/s00894-016-2933-0. Epub 2016 Mar 11.