Template-based protein structure modeling using the RaptorX web server

被引:1211
作者
Kaellberg, Morten [1 ,2 ]
Wang, Haipeng [1 ]
Wang, Sheng [1 ]
Peng, Jian [1 ]
Wang, Zhiyong [1 ]
Lu, Hui [2 ]
Xu, Jinbo [1 ]
机构
[1] Toyota Technol Inst, Chicago, IL USA
[2] Univ Illinois, Dept Bioengn, Chicago, IL USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
STRUCTURE PREDICTION; SECONDARY STRUCTURE; HOMOLOGY DETECTION; FOLD RECOGNITION; RESIDUE-LEVEL; I-TASSER; DATABASE; SEQUENCES; ACCURATE; ALIGNMENT;
D O I
10.1038/nprot.2012.085
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
A key challenge of modern biology is to uncover the functional role of the protein entities that compose cellular proteomes. To this end, the availability of reliable three-dimensional atomic models of proteins is often crucial. This protocol presents a community-wide web-based method using RaptorX (http://raptorx.uchicago.edu/) for protein secondary structure prediction, template-based tertiary structure modeling, alignment quality assessment and sophisticated probabilistic alignment sampling. RaptorX distinguishes itself from other servers by the quality of the alignment between a target sequence and one or multiple distantly related template proteins (especially those with sparse sequence profiles) and by a novel nonlinear scoring function and a probabilistic-consistency algorithm. Consequently, RaptorX delivers high-quality structural models for many targets with only remote templates. At present, it takes RaptorX similar to 35 min to finish processing a sequence of 200 amino acids. Since its official release in August 2011, RaptorX has processed similar to 6,000 sequences submitted by similar to 1,600 users from around the world.
引用
收藏
页码:1511 / 1522
页数:12
相关论文
共 51 条
[1]   Mass spectrometry-based proteomics [J].
Aebersold, R ;
Mann, M .
NATURE, 2003, 422 (6928) :198-207
[2]   Data growth and its impact on the SCOP database: new developments [J].
Andreeva, Antonina ;
Howorth, Dave ;
Chandonia, John-Marc ;
Brenner, Steven E. ;
Hubbard, Tim J. P. ;
Chothia, Cyrus ;
Murzin, Alexey G. .
NUCLEIC ACIDS RESEARCH, 2008, 36 :D419-D425
[3]  
[Anonymous], 1993, Statistical Language Learning
[4]   The ENZYME database in 2000 [J].
Bairoch, A .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :304-305
[5]   Protein structure prediction and structural genomics [J].
Baker, D ;
Sali, A .
SCIENCE, 2001, 294 (5540) :93-96
[6]  
Bateman A, 2004, NUCLEIC ACIDS RES, V32, pD138, DOI [10.1093/nar/gkp985, 10.1093/nar/gkh121, 10.1093/nar/gkr1065]
[7]   The Protein Data Bank [J].
Berman, HM ;
Westbrook, J ;
Feng, Z ;
Gilliland, G ;
Bhat, TN ;
Weissig, H ;
Shindyalov, IN ;
Bourne, PE .
NUCLEIC ACIDS RESEARCH, 2000, 28 (01) :235-242
[8]   A METHOD TO IDENTIFY PROTEIN SEQUENCES THAT FOLD INTO A KNOWN 3-DIMENSIONAL STRUCTURE [J].
BOWIE, JU ;
LUTHY, R ;
EISENBERG, D .
SCIENCE, 1991, 253 (5016) :164-170
[9]   Protein annotation and modelling servers at University College London [J].
Buchan, D. W. A. ;
Ward, S. M. ;
Lobley, A. E. ;
Nugent, T. C. O. ;
Bryson, K. ;
Jones, D. T. .
NUCLEIC ACIDS RESEARCH, 2010, 38 :W563-W568
[10]   NAPS: a residue-level nucleic acid-binding prediction server [J].
Carson, Matthew B. ;
Langlois, Robert ;
Lu, Hui .
NUCLEIC ACIDS RESEARCH, 2010, 38 :W431-W435