MS Annika: A New Cross-Linking Search Engine.

Georg J Pirklbauer,Manuel Matzinger,Viktoria Dorfer,Stephan Winkler,Karl Mechtler,Christian E Stieger

doi:10.1021/acs.jproteome.0c01000

Georg J Pirklbauer, Manuel Matzinger + Show 4 more

Open Access

https://doi.org/10.1021/acs.jproteome.0c01000

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Abstract

Cross-linking mass spectrometry (XL-MS) has become a powerful technique that enables insights into protein structures and protein interactions. The development of cleavable cross-linkers has further promoted XL-MS through search space reduction, thereby allowing for proteome-wide studies. These new analysis possibilities foster the development of new cross-linkers, which not every search engine can deal with out of the box. In addition, some search engines for XL-MS data also struggle with the validation of identified cross-linked peptides, that is, false discovery rate (FDR) estimation, as FDR calculation is hampered by the fact that not only one but two peptides in a single spectrum have to be correct. We here present our new search engine, MS Annika, which can identify cross-linked peptides in MS2 spectra from a wide variety of cleavable cross-linkers. We show that MS Annika provides realistic estimates of FDRs without the need of arbitrary score cutoffs, being able to provide on average 44% more identifications at a similar or better true FDR than comparable tools. In addition, MS Annika can be used on proteome-wide studies due to fast, parallelized processing and provides a way to visualize the identified cross-links in protein 3D structures.

Highlights

Cross-linking mass spectrometry (XL-MS) allows for the identification of protein−protein interactions as well as protein structure.[1]
We present a new search engine, MS Annika, for the identification of cross-links from tandem MS data, which is transparent in peptide identification and reliable in false discovery rate (FDR) calculation
We here present results obtained with our new search engine MS Annika capable of reliably identifying cross-linked peptides, suitable for a variety of cleavable cross-linkers and qualified to properly estimate the underlying FDR

Summary

Introduction

Cross-linking mass spectrometry (XL-MS) allows for the identification of protein−protein interactions as well as protein structure.[1] Until now, these two problems were tackled by individual methods that are usually expensive or timeconsuming, such as NMR and X-ray crystallography.[2] Very recently, computational approaches to estimate protein structures have shown large potential but remain to be thoroughly evaluated.[3] With the emergence of cross-linking technology, these two areas of interest can be investigated with one technique. In XL-MS, linker molecules are used to connect one or more residues of one or more proteins (usually two). There are many different types of linkers, which can be grouped into MScleavable and noncleavable linkers.[8] The initially developed linkers were noncleavable linkers, realized as sturdy connections between two residues. Cleavable cross-linkers are an extension of this idea but enable cleavage of specific position in the linker molecule, allowing for increased speeds and confidence in data analysis.[1]

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