Abstract
Proteomes may be composed of a million or more protein species. Finding and quantifying a single protein in samples of this complexity is a great challenge for liquid chromatography-mass spectrometry (LC-MS) systems. This problem is complicated by the fact that proteomes bear proteoform families that vary slightly in primary, secondary, or tertiary structure and posttranslational modifications. Moreover, members of these families often vary in biological activity. The fact that many proteoforms are not in sequence libraries is a further problem. All of these variables complicate the interpretation of LC-MS data. A problem with LC-MS systems is that irrespective of their resolving power they lack the ability to select molecular species for analysis on a structural basis. It would be of great value to group polypeptides for analysis according to structural features instead of identifying those features after an analysis is completed. An analogy is that enormous physical dexterity is dwarfed in searching for needles in a hay stack by the use of a magnet to pull them out of the hay. The objective in this chapter is to describe technologies that select polypeptides and PTM-bearing variants from mixtures on the basis of their structure prior to or as a part of LC-MS analyses. Clearly, affinity selection methods will play a major role in the future of proteomics and clinical diagnostics.
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