Journal
ANALYTICAL CHEMISTRY
Volume 88, Issue 20, Pages 9949-9957Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.6b01585
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Funding
- KUL-Spa (Onderzoekstoelagen)
- KUL-Spa (Bijzonder Onderzoeksfonds)
- KUL-Spa (KU Leuven)
- RiMembR (Vlaanderen Onderzoeksprojecten) [G006814N]
- RiMembR (FWO)
- Ghent University [BOF12/GOA/014]
- PRIME-XS Project - European Union [262067]
- Deutsche Forschungsgemeinschaft [FOR 1905, FOR 1352]
- Excellence Initiative of the German Federal and State Governments [EXC 294]
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Chemical cross-linking coupled with mass spectrometry plays an important role in unravelling protein interactions, especially weak and transient ones. Moreover, crosS-linking complements several structural determination approaches such as cryo:EM. Although several computational approaches are available for the annotation of spectra obtained from cross-linked peptides, there remains room for improvement. Here, we present Xilmass, a novel algorithm to identify cross-linked peptides that introduces two new concepts: (i) the cross-linked peptides are represented in the search database such that the cross-linking sites are explicitly encoded, and (ii) the scoring function derived from the Andromeda algorithm was adapted to score against a theoretical tandem mass spectrometry (MS/MS) spectrum that contains the peaks from all possible fragment ions of a cross-linked peptide pair. The performance of Xilmass was evaluated against the recently published Kojak and the popular pLink algorithms on a calmodulin-plectin complex data set, as well as three additional, published: data sets. The results show that Xilmass typically had cross-linked sites and also the highest number of predicted cross-linked sites.
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