bbc 2015

BeNeLux Bioinformatics Conference – Antwerp, December 7-8 2015
Abstract ID: O12
Oral presentation
10th Benelux Bioinformatics Conference bbc 2015
O12. XILMASS: A CROSS-LINKED PEPTIDE IDENTIFICATION ALGORITHM
Şule Yılmaz 1,2,3* , Masa Cernic 4 , Friedel Drepper 5 , Bettina Warscheid 5 , Lennart Martens 1,2,3 & Elien Vandermarliere 1,2,3 .
Medical Biotechnology Center, VIB, Ghent, Belgium 1 ; Department of Biochemistry, Ghent University, Ghent, Belgium 2 ;
Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium 3 ; Department of Biochemistry, Molecular and
Structural Biology, Jožef Stefan Institute, Ljubljana, Slovenia 4 ; Functional Proteomics and Biochemistry, Department of
Biochemistry and Functional Proteomics, Institute for Biology II and BIOSS Centre for Biological Signaling Studies,
University of Freiburg, Freiburg, Germany 5 . *sule.yilmaz@ugent.be
Chemical cross-linking coupled with mass spectrometry (XL-MS) facilitates the determination of protein structure and
the understanding of protein interactions. The current computational approaches rely on different strategies with a limited
number of open-source and easy-to-use search algorithms. We therefore built a novel cross-linked peptide identification
algorithm, called Xilmass which has a novel database construction and a new scoring function adapted from traditional
database search algorithms. We compared the performance of Xilmass against one of the most popular and publicly
available algorithms: pLink, and a recently published algorithm Kojak. We found that Xilmass identified 140 spectra
whereas Kojak and pLink identified 119 and 35, respectively. We mapped the cross-linking sites on the structure which
resulted in the identification of 20 possible cross-linking sites. These findings show that Xilmass allows the identification
of cross-linking sites.
INTRODUCTION
The structure of a protein is crucial for its functionality.
Protein structure is commonly determined by X-ray
crystallography or nuclear magnetic resonance (NMR). X-
ray crystallography is only feasible for crystallizable
proteins and NMR has a protein size limitation. Due to
these restrictions, protein complexes are much more
difficult to approach with these classical methods.
However, chemical cross-linking of the complex coupled
with mass spectrometry (XL-MS) allows to study of these
protein complexes. The identification of the measured
fragmentation spectra is a challenging task. One approach
to identify cross-linked peptides is to linearize crosslinked
peptide-pairs in order to generate a database to
perform traditional search engines (Maiolica et al., 2007).
However, a traditional search engine is not directly
applicable to identify cross-linked peptides. Another
approach is to rely on the usage of labeled cross-linkers,
but this has a decreased performance when unlabeled
cross-linkers are used. We therefore built an algorithm,
Xilmass, which is designed for the identification of XL-
MS fragmentation spectra without linearization of peptides
and the requirement of labeled cross-linkers. We also
introduced a new way of representation of a cross-linked
peptide database and directly implemented a new scoring
function.
METHODS
The data sets were derived from human calmodulin (CaM)
and the actin binding domain of plectin (plectin-ABD)
which were cross-linked by DSS. The data sets were
analyzed on a Velos Orbitrap Elite.
Cross-linked peptides were identified by Xilmass, pLink
(Yang et al., 2012) and Kojak (Hoopmann et al., 2015).
The identifications of both Xilmass and Kojak were
validated by Percolator (Käll et al., 2007) at q-value=0.05.
pLink returned a validated list at FDR=0.05.
The findings on cross-linking sites were validated with the
aid of the available structures (Plectin PDB-entry: 4Q57
and calmodulin PDB-entry: 2F3Y). The cross-linking sites
were predicted by X-Walk (Kahraman et al., 2011) and
PyMOL was used for the visualization.
RESULTS & DISCUSSION
We compared the number of identified spectra and crosslinking
sites from Xilmass, pLink and Kojak. Xilmass
identified 140 spectra whereas Kojak and pLink identified
119 and 35 spectra, respectively (at FDR=0.05). Xilmass
identified 53 cross-linking sites from the 140 spectra with
37 obtained from at least 2 peptide-to-spectrum matches
(PSMs). Kojak identified more cross-linking sites (60),
however, only 26 cross-linking sites have at least 2 PSMs.
The identified cross-linking sites by Xilmass were
manually verified on the structure (Figure1). We defined
20 cross-linking sites as possible (Cα-Cα distances within
30Å (orange)) and not-predicted (Cα-Cα distances
exceeding 30Å (blue)). These findings show that Xilmass
allows the identification of cross-linking sites.
FIGURE 1. The identified cross-linking sites were mapped on the plectin
protein structure to manually verify them (PDB-entry:4Q57)
REFERENCES
Hoopmann ,M R et al. Journal of Proteome Research, 14, 2190–2198
(2015)
Kahraman,A. et al. Bioinformatics, 27, 2163–2164 (2011)
Käll,L. et al. Nature Methods, 4, 923–925 (2007)
Maiolica,A. et al. Molecular & cellular proteomics:MCP, 6, 2200–2211
(2007)
Yang,B. et al. Nature Methods, 9, 904–906 (2012)
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