Yeah! Been waiting to talk about this one!
Paper first: It is from (Jane) Zheng Zhang et al., out of Steve Stein's lab (and some guy named Markey was involved as well). Its in this month's JPR.
Spectral libraries are faster than general search algorithms and they have great levels of confidence. This is because you aren't looking at theoretical spectra generated on the fly. You are either looking at real observed MS/MS spectra or you are looking at spectra that are informed by real-life MS/MS spectra. (There are fully in silico developed spectral libraries out there, too, but this doesn't count here).
Downside? You have to have a darned spectral library that is relevant to your experiment. For example, you know the hundreds or thousands of iTRAQ labeled cancer cell line runs in repositories people have put in? Great data to pull spectral libraries from -- if you are doing iTRAQ. If you want to use TMT so you can have more channels you're out of luck cause you can't search that data against any of those libraries...
What this study shows is that --HEY! The peptide backbone fragments the same way whether its TMT or iTRAQ labeled. And if you just pull the spectral library and convert (clean) it to keep the peptides that will stay (and are experimentally observed) and mass shift the ones that will change thanks to the tag, it works almost as well as running a sample with the correct reagent and original library!
Work is going on at NIST to take libraries and convert them for direct searching. They also state in the paper that spectral library searching that can utilize PTMs are in works! Yeah!
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