Proteomic databases

Pineda, F. J. Lin, J. S. Fenselau, C. Dimerov, P. A. Testing the significance of microorganism identification by mass spectrometry and proteome database search. Anal. Chem. 2000, 72, 3739-3744. 

Dworzanski, J. R Snyder, A. P. Chen, R. Zhang, H. Wishart, D. Li, L. Identification of bacteria using tandem mass spectrometry combined with a proteome database and statistical scoring. Anal. Chem. 2004,76,2355-2366. 

Scharfe C et al. MITOP, the mitochondrial proteome database 2000 update. Nucleic Acids Res 2000 28 155-158. Molloy MP et al. Establishment of the human reflex tear two-dimensional polyacrylamide gel electrophoresis reference map new proteins of potential diagnostic value. Electrophoresis 1997 18 2811-2815. 

Katz S, Harris R, Lau JT, Chau A, The use of gene expression analysis and proteomic databases in the development of a screening system to determine the value of natural medicinal products, Evid Based Complement Alternat Med 3 65-70,2006. 

Human Proteinpedia (59, is a proteomic database with a public... 

Key words Cancer, Personalized medicine. Biomarker, Proteome, Database... 

The main goal of the proteomic research is to find the distinction between quantitative regulation and structural proteomics. Today, the core technology of proteomics is 2DE (two-dimensional electrophoresis) coupled with MS (mass spectrometry). It offers the most widely accepted way of gathering qualitative and quantitative protein behavioral data in cells, tissues, and fluids to form proteomic databases. 

Currently available MS instruments are much more suitable for peptide analysis and the data obtained can be directly used for comparison with protein sequences derived from proteome databases. 

Gromov, P.S., Ostergaard, M., Gromova, I., Celis, J.E. (2002). Human proteomic databases, a powerful resource for functional genomics in health and disease. Prog. Biophys. Mol. Biol., 80, 3-22. 

Computation proteome annotation is the process of proteome database mining, which includes structure/fold prediction and functionality assignment. Methodologies of secondary structure prediction and problems of protein folding are discussed. Approaches to identify functional sites are presented. Protein structure databases are surveyed. Secondary structure predictions and pattern/fold recognition of proteins using the Internet resources are described. 

Prokisch H, Andreoli C, Ahting U, Heiss K, Ruepp A, et al. 2006. Mitop2 The mitochondrial proteome database -now including mouse data. Nucleic Acids Res 34 D705-D711. 

The mentioned data management systems are only first steps toward comprehensive lipid databases and global lipid networks. An example for such a data bank is LIPIDMAPS (http //www.lipidmaps.org), which covers structures and annotations of biologically relevant lipids (43). The structures originate from the core laboratories of the LIPIDMAPS consortium and their partners. In this database, users can search the LIPID MAPS proteome database using either text-based or structure-based search options. In addition to LIPIDMAPS, other databases in Europe (http //www.lipidomics.net) and Japan (http //www.lipidbank.jp) have been initiated. 

Several of the above methods significantly increase the size of proteomic databases. This causes a decrease in peptide identification sensitivity (111,130), complicates protein inference (because of many redundant sequences) (160,161), and leads to longer search times. Although some efforts have been made to optimize search speeds (162), these hurdles remain unsolved. 

The links provided by the SWISS-PROT entries to other proteomics databases like SWISS-2DPAGE, PROSITE/InterPro and about 30 other databases allow for rapid access to experimental proteomic data, like position and number of protein spots on a 2-D gel, other members of the same family, or the 3-D structure of the protein, etc. 

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