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• W2523745900 abstract "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 the highest number of identified distinct cross-linked sites and also the highest number of predicted cross-linked sites." @default.
• W2523745900 created "2016-09-30" @default.
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• W2523745900 date "2016-09-28" @default.
• W2523745900 modified "2023-10-16" @default.
• W2523745900 title "Xilmass: A New Approach toward the Identification of Cross-Linked Peptides" @default.
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• W2523745900 doi "https://doi.org/10.1021/acs.analchem.6b01585" @default.
• W2523745900 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27642655" @default.
• W2523745900 hasPublicationYear "2016" @default.
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