title: ECL: an exhaustive search tool for the identification of cross-linked peptides using whole database.
abstract: BACKGROUND
  Chemical cross-linking combined with mass spectrometry (CX-MS) is a high-throughput approach to studying protein-protein interactions. The number of peptide-peptide combinations grows quadratically with respect to the number of proteins, resulting in a high computational complexity. Widely used methods including xQuest (Rinner et al., Nat Methods 5(4):315-8, 2008; Walzthoeni et al., Nat Methods 9(9):901-3, 2012), pLink (Yang et al., Nat Methods 9(9):904-6, 2012), ProteinProspector (Chu et al., Mol Cell Proteomics 9:25-31, 2010; Trnka et al., 13(2):420-34, 2014) and Kojak (Hoopmann et al., J Proteome Res 14(5):2190-198, 2015) avoid searching all peptide-peptide combinations by pre-selecting peptides with heuristic approaches. However, pre-selection procedures may cause missing findings. The most intuitive approach is searching all possible candidates. A tool that can exhaustively search a whole database without any heuristic pre-selection procedure is therefore desirable.
  
  
  RESULTS
  We have developed a cross-linked peptides identification tool named ECL. It can exhaustively search a whole database in a reasonable period of time without any heuristic pre-selection procedure. Tests showed that searching a database containing 5200 proteins took 7 h. ECL identified more non-redundant cross-linked peptides than xQuest, pLink, and ProteinProspector. Experiments showed that about 30 % of these additional identified peptides were not pre-selected by Kojak. We used protein crystal structures from the protein data bank to check the intra-protein cross-linked peptides. Most of the distances between cross-linking sites were smaller than 30 Å.
  
  
  CONCLUSIONS
  To the best of our knowledge, ECL is the first tool that can exhaustively search all candidates in cross-linked peptides identification. The experiments showed that ECL could identify more peptides than xQuest, pLink, and ProteinProspector. A further analysis indicated that some of the additional identified results were thanks to the exhaustive search.
authors.affiliation: Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.
authors.forename: Fengchao
authors.initials: F
authors.lastname: Yu
authors.affiliation: Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong, China. boningli@ust.hk.
authors.forename: Ning
authors.initials: N
authors.lastname: Li
authors.affiliation: Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Hong Kong, China. eeyu@ust.hk.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China. eeyu@ust.hk.
authors.forename: Weichuan
authors.initials: W
authors.lastname: Yu
mesh_terms: D003432:Cross-Linking Reagents / Q000737:chemistry*; D030562:Databases, Protein; D006801:Humans; D010455:Peptides / Q000737:chemistry*; D057386:Search Engine
chemical_list: D003432:Cross-Linking Reagents; D010455:Peptides
keywords: Cross-linking; Database searching; Peptide identification