MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics

By Andy T. Kong, F. V. Leprevost, Dmitry Avtonomov, Dattatreya Mellacheruvu, Alexey I. Nesvizhskii. Nature Methods, 2017

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There is a need to better understand and handle the 'dark matter' of proteomics—the vast diversity of post-translational and chemical modifications that are unaccounted in a typical mass spectrometry–based analysis and thus remain unidentified. We present a fragment-ion indexing method, and its implementation in peptide identification tool MSFragger, that enables a more than 100-fold improvement in speed over most existing proteome database search tools. Using several large proteomic data sets, we demonstrate how MSFragger empowers the open database search concept for comprehensive identification of peptides and all their modified forms, uncovering dramatic differences in modification rates across experimental samples and conditions. We further illustrate its utility using protein–RNA cross-linked peptide data and using affinity purification experiments where we observe, on average, a 300% increase in the number of identified spectra for enriched proteins. We also discuss the benefits of open searching for improved false discovery rate estimation in proteomics.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/3767243e735b57b2f62632aebf1c1d13e629a6f5

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Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial (2018, neutral): “A recent study comparing standard database searching of DDA data with open modification searches of the same data found that this scenario occurs rather infrequently (Kong et al , 2017).”
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