LC-MS in proteomics

In the previous chapter (Ch. 17), key technologies in the LC-MS analysis of peptides and proteins were introduced and discussed. The technologies discussed can be considered as the enabling technologies, at least from the LC-MS point of view, to the current developments in the field of proteomics. 

A large number of review papers were published on tlie role of MS in proteomics or specific application areas within the field. Some of these papers were especially usefol in preparing this chapter and are recommended as further reading [14-18]. The book by Liebler [19] provides a concise overview. The discussion in this chapter provides a technology-oriented review of developments in relation to LC-MS, and is certainly not a comprehensive overview of proteomics. 

Proteomics is the study of the proteome, the expression of the genome in cellular and extracellular proteins, i.e., involving the entire complement of proteins expressed by a particular cell, organism, or tissue. It comprises a transformation of protein chemistry and structure biology, where the structure and function of individual proteins are studied, into systems biology, where partial peptide sequencing is performed in combination with database matching to identify proteins in complex mixtures. The focus has moved to understand the cellular function of proteins. This means that next to identification of which proteins are present, other 

An alternative classification would indicate the areas of profihng, functional, and stractural proteomics, dealing with differential expression of proteins, function of individual proteins and/or protein complexes in the hving cell, and elucidation of the tertiary stracture of proteins in the cell. In this classification, the role of MS would be considered from a different perspective. 

A complementary approach to protein identification is based on peptide seqnencing analysis (PSA) by collision-induced dissociation (CID) in MS-MS. Por proteomics studies, the de novo sequencing of MS-MS spectra is too time-consuming. Therefore, algorithms have been developed to either provide antomated MS-MS spectmm interpretation, or perform protein identification by means of a SEQUEST database search [6-7]. In the latter case, the precursor m/z values are matched against a virtual digestion of all the proteins in the database. Sequence ions are predicted for the peptides that match the precnrsor m/z values, and compared with the measured MS-MS data. A correlation score is calculated for each match. 

---