Shotgun cross-linking analysis for studying quaternary and tertiary protein structures.

We developed a new approach that employs a novel computer algorithm for the sensitive and high-throughput analysis of tertiary and quaternary interaction sites from chemically cross-linked proteins or multi-protein complexes. First, we directly analyze the digests of the chemically cross-linked proteins using only high-accuracy LC-MS/MS data. We analyze these data using a computer algorithm, we term X!Link, to find cross-links between two peptides. Our algorithm is rapid, taking only a few seconds to analyze approximately 5000 MS/MS spectra. We applied this algorithm to analyze cross-linked sites generated chemically using the amino specific reagent, BS3, in both cytochrome c and the mitochondrial division dynamin mutant, Dnm1G385D, which exists as a stable homodimer. From cytochrome c, a well-established test protein, we identified a total of 31 cross-links, 21 interpeptide and 10 intrapeptide cross-links, in 257 MS/MS spectra from a single LC-MS/MS data set. The high sensitivity of this technique is indicated by the fact that all 19 lysines in cytochrome c were detected as a cross-link product and 33% of all the Lys pairs within 20 A were also observed as a cross-link. Analysis of the cross-linked dimeric form of Dnm1G385D identified a total of 46 cross-links, 38 interpeptide and 8 intrapeptide cross-links, in 98 MS/MS spectra in a single LC-MS/MS data set. These results represent the most abundant cross-links identified in a single protein or protein dimer to date. Statistical analysis suggests a 1% false discovery rate after optimization of filtering parameters. Further analysis of the cross-links identified using our approach indicates that careful manual inspection is important for the correct assignment of cross-linking sites when multiple cross-linkable sites or several similar sequences exist. In summary, we have developed a sensitive MS-based approach to identify peptide-peptide cross-links that does not require isotopic labeling or comparison with non-cross-linked controls, making it faster and simpler than current methodologies.