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- Title
Prediction of high-responding peptides for targeted protein assays by mass spectrometry.
- Authors
Fusaro, Vincent A; Mani, D R; Mesirov, Jill P; Carr, Steven A
- Abstract
Protein biomarker discovery produces lengthy lists of candidates that must subsequently be verified in blood or other accessible biofluids. Use of targeted mass spectrometry (MS) to verify disease- or therapy-related changes in protein levels requires the selection of peptides that are quantifiable surrogates for proteins of interest. Peptides that produce the highest ion-current response (high-responding peptides) are likely to provide the best detection sensitivity. Identification of the most effective signature peptides, particularly in the absence of experimental data, remains a major resource constraint in developing targeted MS-based assays. Here we describe a computational method that uses protein physicochemical properties to select high-responding peptides and demonstrate its utility in identifying signature peptides in plasma, a complex proteome with a wide range of protein concentrations. Our method, which employs a Random Forest classifier, facilitates the development of targeted MS-based assays for biomarker verification or any application where protein levels need to be measured.
- Publication
Nature biotechnology, 2009, Vol 27, Issue 2, p190
- ISSN
1546-1696
- Publication type
Journal Article
- DOI
10.1038/nbt.1524