Database Searching with Mass Spectrometry Data

7 Database Searching with Mass Spectrometry Data 

Database searches were performed against a non-redundant NCBI database using Mascot (Matrix Science, London, UK) selecting human and/or rodent species. Parent ion and fragment ion mass tolerances were both set at 0.6 Da. 

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Bottom-up proteomics. This strategy relies on peptide-level information, such as mass or sequence, to identify a protein. Cnrrently, this strategy dominates proteomics research. In this approach, the protein is digested, typically with trypsin, and the digest is analyzed with an appropriate mass spectrometry system to obtain the peptide masses and sequences. The database search with mass spectrometry data characterizes the protein. More details of the mass spectrometry platforms used in this approach are provided in the following sections. 

There are many other methods that can be used to separate proteins before characterization by mass spectrometry. Often in characterizing unknown proteins in a mixture, the constituent polypeptides are first enzymatically digested to yield a mixture of peptides. The peptides then are analyzed by MS either with or without some prior chromatographic or electrophoretic separation. With the aid of database search algorithms, the MS data are then evaluated to identify the proteins represented in the mixture (Abersold and Mann, 2003 Elia et ah, 2005). 

Eng, J. K. Yates, J. R. Schieltz, D. M. Protein database searching with ion trap MS" data. Proceedings of the 43rd Conference on Mass Spectrometry and Allied Topics, Atlanta, GA, May 21-26,1995, p. 641. 

To many, mass spectrometry is synonymous with El mass spectrometry. This view is understandable for two reasons. First, historically, El was universally available before other ionization methods were developed. Much of the early work was El mass spectrometry. Second, the major libraries and databases of mass spectral data, which are relied upon so heavily and cited so often, are of El mass spectra. Some of the readily accesible databases contain El mass spectra of over 390,000 compounds and they are easily searched by efficient computer algorithms. The uniqueness of the El mass spectrum for a given organic compound, even for stereoisomers, is an almost certainty. This uniqueness, coupled with the great sensitivity of the method, is... 

Without any doubt, mass spectrometry is now the most efficient way to identify proteins [75-78], The method is based on comparison of the data obtained from the mass spectrometry with those predicted for all the proteins contained in a database. The efficiency of the method results from the development of mass spectrometry into a rapid and sensitive method to analyse peptides and proteins and also from the availability of larger and larger databases. In October 2006, these databases contained more than 2400000 non-redundant sequences. Furthermore, the data obtained from genomic sequences after translation in the six lecture frames also can be used. The databases based on expressed sequence tags (ESTs) are another usable source for search. They are composed of sequences based on cDNA fast sequencing. They are limited to short lengths, about 300 bases, and contain many errors but they correspond to coding sequences. Despite their defects, they are very useful for identification of proteins by mass spectrometry [79]. 

With the advent of accurate mass instruments, access to a reference database or library of compounds with the exact masses of precursor and product ions is becoming increasingly important. Many instrument manufacturers, as well as independent companies or institutions, are developing software that allows chemists to manage this type of information for specific applications such as proteomics or chemical contaminants. Examples of online resources that may be useful for searching for unknown residues based on molecular formulas obtained from accurate mass data inciude Metlin from the Scripps Center for Mass Spectrometry and ChemSpider from the Royal Society of Chemistry. " ... 

With the aid of freely available Internet tools and databases, the MALDI data set is compared with known proteins to generate a list of potential matches. The analyst inputs the peptidase used to digest the original protein and the m/z values of the peptides displayed in the MALDI spectrum. As specified by the search criteria, the search delivers (in a matter seconds ) a list of peptide sequences and the proteins these sequences contain. Next, a different peptidase is used to hydrolyze the protein, to provide a second set of peptides that are also analyzed by MALDI and matched against the database. MALDI mass spectrometry compares the amino acid composition of unsequenced peptides with the amino acid sequence of known proteins in order to identify an unknown protein. The procedure is repeated until the list of potential matches is narrowed to a single known protein, additional data are needed, or it becomes likely that the protein is new. 

Figure 3 Protein identification by mass spectrometry, in a typicai strategy, digested peptides are anaiyzed by MALDi-TOF-MS in order to determine the masses of intact peptides. These masses can be used in correiative database searches to identify exact matches. If this approach fails, ESI-MS/MS analysis can be used to generate peptide fragment ions. These can be used to search less robust data sources and to produce de novo peptide sequences. (Reproduced with permission from Twyman RM (2004) Principles of Proteomics. Abington, UK Bios/Garland Publishers.)...

NMR data and potentiaUy mass spectrometry, and with N chemical shifts in hand, it is possible to search the ACD/NNMR database using a number of flexible searches to identify potential hits or potential classes of compounds that match the experimental data. Various options can be set in the search interface (see Fig. 12). These include the Looseness Factor, the Minimum Number of Query Shifts, and the Hit Quahty Index (HQI). 

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