RT Journal Article SR Electronic T1 ECL 2.0: Exhaustively Identifying Cross-Linked Peptides with a Linear Computational Complexity JF bioRxiv FD Cold Spring Harbor Laboratory SP 097089 DO 10.1101/097089 A1 Fengchao Yu A1 Ning Li A1 Weichuan Yu YR 2016 UL http://biorxiv.org/content/early/2016/12/28/097089.abstract AB Chemical cross-linking coupled with mass spectrometry is a powerful tool to study protein-protein interactions and protein conformations. Two linked peptides were ionized and fragmented to produce a tandem mass spectrum. In such an experiment, a tandem mass spectrum contains ions from two peptides. The peptide identification problem becomes a peptide pair identification problem. Most tools, however, don’t search all possible pairs due to the long computational time. Consequently, a significant proportion of all linked peptides are missed. In our earlier work, we developed a tool named ECL to search all pairs of peptides exhaustively. However, compared to tools only pairing a small number of peptides, ECL is still too slow when the database is large.Here, we propose an advanced version of ECL, named ECL 2.0. It achieves linear time and space complexity by taking advantage of the additive property of a score function. It can exhaustively search tens of thousands of spectra against a database containing thousands of proteins in a few hours. Among another four state-of-the-art tools, ECL 2.0 is much faster than pLink, StavroX, and ProteinProspector, but slower than Kojak which, however, only searches the smallest proportion of all peptide-peptide pairs among the five tools.