期刊文献+

蛋白质折叠类型分类方法及分类数据库 被引量:5

Protein fold type classify methods and classification database2
下载PDF
导出
摘要 蛋白质折叠规律研究是生命科学重大前沿课题,折叠分类是蛋白质折叠研究的基础。目前的蛋白质折叠类型分类基本上靠专家完成,不同的库分类并不相同,迫切需要一个建立在统一原理基础上的蛋白质折叠类型数据库。本文以ASTRAL-1.65数据库中序列同源性在25%以下、分辨率小于2.5的蛋白为基础,通过对蛋白质空间结构的观察及折叠类型特征的分析,提出以蛋白质折叠核心为中心、以蛋白质结构拓扑不变性为原则、以蛋白质折叠核心的规则结构片段组成、连接和空间排布为依据的蛋白质折叠类型分类方法,建立了低相似度蛋白质折叠分类数据库——LIFCA,包含259种蛋白质折叠类型。数据库的建立,将为进一步的蛋白质折叠建模及数据挖掘、蛋白质折叠识别、蛋白质折叠结构进化研究奠定基础。 The research on protein folding is in the frontier of life science,fold classification is the foundation of protein folding study Nowadays protein fold classification rely on experts,different database have different classification standards,so it is very important for us to build a protein folding database under the same criteria.this paper based on database ASTRAL-1.65,according to sequence homology below 25%,resolution below 2.5 and the three dimensional structure of protein and fold type characteristics analysis we put forward a protein fold type classification method which based on protein fold core,under the protein structure topology invariant,which according to protein fold core regular structure composition,connection and spatial arrangement.We established low identity protein fold classification database——LIFCA,which contains 259 protein fold types.The established of this database lay the foundation for our future works on protein fold modeling,date mining,protein fold Identification and protein fold structure evolution.
出处 《生物信息学》 2010年第3期245-247,253,共4页 Chinese Journal of Bioinformatics
基金 国家自然科学基金(30570427) 北京市自然科学基金(4092008)
关键词 蛋白质折叠 折叠类型分类 数据库 折叠核心 低相似度 Protein fold Fold type classification Database Fold core Low identity
  • 相关文献

参考文献14

  • 1Chothia C.One thousand families for the molecular biologist[J].Nature,1992,357(6379):543-544.
  • 2David Baker.A surprising simplicity to protein folding[J].Nature,2000.
  • 3Daggett V,Fersht A.The present view of the mechanism of protein folding[J].Nat Rev Mol Cell Biol,2003,4(6):497-502.
  • 4Daggett V,Fersht A.Is there a unifying mechanism for protein folding?[J].Trends Biochem Sci,2003,28(1):18-25.
  • 5Gianni S,Guydosh N R,Khan F,et al.Unifying features in protein-folding mechanisms[J].Proc Natl Acad Sci USA,2003,100(23):13286-13291.
  • 6Onuchic J N,Wolynes P G.Theory of protein folding[J].Curr Opin Struct Biol,2004,14(1):70-75.
  • 7Chandonia JM,Hon G,Walker NS,Lo Conte L,Koehl P,Levitt M,Brenner SE.The ASTRAL compendium in 2004.Nucleic Acids Research,2004,32(Sp.Iss.SI):D189-D192.
  • 8Murzin A G,Brenner S E,Hubbard T,et al.SCOP:a structural classification of proteins database for the investigation of sequences and structures[J].J.Mol.Biol.,1995,(247):536-540.
  • 9Lo Conte L,Brenner S E,Hubbard T,et al.SCOP database in 2002:refinements accommodate structural genomics[J].Nucl.Acid Res,2002,30(1):264-267.
  • 10C A.Orengo,A D.Michie,S.Jones,et al.CATH:A Hierarchic Classification of Protein Domain Structures[J].J.M.Structure,1997,5(8):1093-1108.

二级参考文献47

  • 1施建宇,潘泉,张绍武,梁彦.基于支持向量机融合网络的蛋白质折叠子识别研究[J].生物化学与生物物理进展,2006,33(2):155-162. 被引量:19
  • 2李菁,王炜.氨基酸残基归类及用简化后的字符识别蛋白质结构保守区域[J].中国科学(C辑),2006,36(6):552-562. 被引量:1
  • 3[2]Chothia C.One thousand families for the molecular biologist.Nature,1992,357(6379):543~544
  • 4[3]Baker D.A surprising simplicity to protein folding.Nature,2000,405(6782):39~42
  • 5[4]Ding CHQ,Dubchak L Multi-class protein fold recognition using support vector machines and neural networks.Bioinformatics,2001,17(4):349~358
  • 6[7]Bowie JU,Luthy R,Eisenberg D.A method to identify protein sequences that fold into a known three-dimensional structure.Science,1991,253:164~170
  • 7[8]Elofsson A,Fischer D,Rice DW,Le Grand S.A study of combined structure-sequence profiles.Folding & Design,1998,1:451~461
  • 8[9]Jones DT,Taylor WR,hornton JM.A new approach to protein fold recognition.Nature,1992,358:86~89
  • 9[10]Bryant SH,Lawrence CE.An empirical energy function for threading protein sequence through folding motif.Proteins,1993,16:92~112
  • 10[11]Mirny LA,Shakhnovich EI.Protein structure prediction by threading:why it works and why it does not.Mol Biol,1998,283:507~526

共引文献9

同被引文献43

  • 1张玮,李晓琴,徐海松,任文科.蛋白质折叠类型识别方法研究[J].生物物理学报,2008,24(1):65-71. 被引量:5
  • 2施建宇,潘泉,张绍武,梁彦.基于支持向量机融合网络的蛋白质折叠子识别研究[J].生物化学与生物物理进展,2006,33(2):155-162. 被引量:19
  • 3TORDA A E. Perspectives in protein-fold recognition[ J]. Current Opinion in Structural Biology, 1997, 7 (2) : 200-205.
  • 4FINKELSTEIN A V. Protein structure: what it is possible to predict now[ J]. Current Opinion in Structural Biology, 1997, 7: 60-71.
  • 5JONES D. Progress in protein structure prediction[ Jl. Current Opinion in Structural Biology, 1997, 7: 377-387.
  • 6CHOTHIA C. One thousand families for the molecular biologist[ J ]. Nature, 1992, 357 (6379) : 543-544.
  • 7LI H, HELLING R, TANG C, et al. Emergence of preferred structures in a simple model of protein folding[ Jl. Science, 1996, 273 : 666-669.
  • 8DAVID B. A surprising simplicity to protein folding[ J 1 ~ Nature, 2000, 405 (6782) : 39-42.
  • 9ALTSCHUL S F, MADDEN T L, SCHAFFER A A, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs[ J]. Nucleic Acids Research, 1997, 25 (17) : 3389-3402.
  • 10EISENBERG D. Into the black of night[J]. Nat Struct Biol, 1997, 4: 95-97.

引证文献5

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部