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A number of successful multiple reaction monitoring (MRM)-directed MS/MS methods for protein characterization and quantification have been published over the past couple of years. These methods have been created either by the generation of in silico MRM transitions or from taking discovery data generated by automated MS/MS analysis and formulating MRM transitions from this. However, such a workflow, where a vast amount of discovery data needs to be searched for idealized MS/MS to target peptides, is difficult and time consuming. Automation of this would simplify the whole workflow, and allowing methods to be created smarter by utilizing the data of peptides that have been previously identified, provides a better chance of success.
In this poster we highlight one possible workflow for the processing of a number of database search results that were generated during proteomic analysis of a complex sample. Proteins identified as of potential interest in these results were then added to a MRM method-building list, and all MS/MS associated with those proteins were extracted from the general proteomic search results.
These MS/MS are then automatically processed to create instrument methods for MRM-directed MS/MS quantification. After analysis of the sample by these methods, the data are processed, both from a sequence identification and a chromatographic LC-MRM peak signal-to-noise perspective. These data are associated with the original proteomic workflow data, allowing visualization of the results and construction of a method that can then undergo validation.