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A specialised proteomic database for comparing matrix‐assisted laser desorption/ionization‐time of flight mass spectrometry data of tryptic peptides with corresponding sequence database segments
Author(s) -
Weiller Georg F.,
Djordjevic Michael J.,
Caraux Gilles,
Chen Hanchai,
Weinman Jeremy J.
Publication year - 2001
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/1615-9861(200111)1:12<1489::aid-prot1489>3.0.co;2-d
Subject(s) - mass spectrometry , sequence database , peptide mass fingerprinting , chemistry , matrix assisted laser desorption/ionization , database , database search engine , peptide sequence , proteomics , time of flight mass spectrometry , bottom up proteomics , sinorhizobium meliloti , protein mass spectrometry , chromatography , biochemistry , ionization , tandem mass spectrometry , desorption , computer science , ion , gene , organic chemistry , adsorption , information retrieval , mutant , search engine
We have developed a specialised proteomic database for the analysis of matrix‐assisted laser desorption/ionization‐time of flight mass spectrometry (MALDI‐TOF MS) data derived from tryptic peptides of Sinorhizobium meliloti proteins. This database currently contains the amino acid sequence data of the proteins predicted from the complete chromosome, MALDI‐TOF MS data from proteolytic peptides of about 400 tryptically digested proteins, and the results of a search of the MALDI‐TOF MS spectra against the chromosomal amino acid sequences. The database made it possible to access and compare the sequences of theoretical tryptic peptides that correspond to MALDI‐TOF peaks in the mass spectrum with predicted tryptic peptides from identified proteins that could not be matched to MALDI‐TOF peaks. A comparison of the molecular weights, isoelectric points and amino acid compositions of the identified and nonidentified peptides is presented. We also show how the system can assist in the development of an automated scoring function that facilitates and consolidates protein identification.