In silico proteome analysis to facilitate proteomics experiments using mass spectrometry

被引:66
作者
Gerard Cagney
Shiva Amiri
Thanuja Premawaradena
Micheal Lindo
Andrew Emili
机构
[1] Program in Proteomics/Bioinformatics, Banting/Best Dept. of Medical Res., University of Toronto, Toronto, Ont.
[2] Dept. of Molecular/Medical Genetics, University of Toronto, Toronto, Ont.
[3] Dept. of Clinical Pharmacology, Royal College of Surgeons, Dublin 2
关键词
Bioinformatics; Mass spectrometry; Model organism; Peptide; Post-translational modification; Proteome;
D O I
10.1186/1477-5956-1-5
中图分类号
学科分类号
摘要
Proteomics experiments typically involve protein or peptide separation steps coupled to the identification of many hundreds to thousands of peptides by mass spectrometry. Development of methodology and instrumentation in this field is proceeding rapidly, and effective software is needed to link the different stages of proteomic analysis. We have developed an application, proteogest, written in Perl that generates descriptive and statistical analyses of the biophysical properties of multiple (e.g. thousands) protein sequences submitted by the user, for instance protein sequences inferred from the complete genome sequence of a model organism. The application also carries out in silico proteolytic digestion of the submitted proteomes, or subsets thereof, and the distribution of biophysical properties of the resulting peptides is presented. proteogest is customizable, the user being able to select many options, for instance the cleavage pattern of the digestion treatment or the presence of modifications to specific amino acid residues. We show how proteogest can be used to compare the proteomes and digested proteome products of model organisms, to examine the added complexity generated by modification of residues, and to facilitate the design of proteomics experiments for optimal representation of component proteins. © 2003 Cagney et al; licensee BioMed Central Ltd.
引用
收藏
页数:15
相关论文
共 23 条
[1]  
Aebersold R., Mann M., Mass spectrometry-based proteomics, Nature, 422, pp. 198-207, (2003)
[2]  
Phizicky E., Bastiaens P.I.H., Zhu H., Snyder M., Fields S., Protein analysis on a proteomic scale, Nature, 422, pp. 208-215, (2003)
[3]  
Tyers M., Mann M., From genomics to proteomics, Nature, 422, pp. 193-197, (2003)
[4]  
Clauser K.R., Baker P.R., Burlingame A.L., Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching, Anal. Chem., 14, pp. 2871-2882, (1999)
[5]  
Eng J.K., McCormack A.L., Yates III J.R., An approach to corelate tandem mass spectral data of peptides with amino acid sequences in a protein database, J. Am. Soc. Mass Spectrom, 5, pp. 976-989, (1994)
[6]  
Washburn M.P., Wolters D., Yates III J.R., Large-scale analysis of the yeast proteome by multidimensional protein identification technology, Nature Biotechnol., 19, pp. 242-247, (2001)
[7]  
Salomon A.R., Ficarro S.B., Brill L.M., Brinker A., Phung Q.T., Ericson C., Sauer K., Brock A., Horn D.M., Schultz P.G., Peters E.C., Profiling of tyrosine phosphorylation pathways in human cells using mass spectrometry, Proc. Natl. Acad. Sci USA, 100, pp. 443-448, (2003)
[8]  
Ficarro S.B., McCleland M.L., Stukenbery P.T., Burke D.J., Ross M.M., Shabanowitz J., Hunt D.F., White F.M., Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae, Nature Biotechnol., 20, pp. 301-305, (2002)
[9]  
MacCoss M.J., McDonald W.H., Saraf A., Sadygov R., Clark J.M., Tasto J.J., Gould K.L., Wolters D., Washburn M., Weiss A., Clark J.I., Yates III J.R., Shotgun identification of protein modifications from protein complexes and lens tissue, Proc. Natl. Acad. Sci. USA, 99, pp. 7900-7905, (2002)
[10]  
Mann M., Jensen O.N., Proteomic analysis of post-translational modifications, Nature Biotechnol., 21, pp. 255-261, (2003)