xComb: A Cross-Linked Peptide Database Approach to Protein−Protein Interaction Analysis
Alexandre Panchaud, Pragya Singh, Scott A. Shaffer, David R. Goodlett
Abstract
Alexandre Panchaud, Pragya Singh, Scott A. Shaffer, David R. Goodlett
Abstract
We developed an informatic method to identify tandem mass spectra composed of chemically cross-linked peptides from those of linear peptides and to assign sequence to each of the two unique peptide sequences. For a given set of proteins the key software tool, xComb, combs through all theoretically feasible cross-linked peptides to create a database consisting of a subset of all combinations represented as peptide FASTA files. The xComb library of select theoretical cross-linked peptides may then be used as a database that is examined by a standard proteomic search engine to match tandem mass spectral data sets to identify cross-linked peptides. The database search may be conducted against as many as 50 proteins with a number of common proteomic search engines, e.g. Phenyx, Sequest, OMSSA, Mascot and X!Tandem. By searching against a peptide library of linearized, cross-linked peptides, rather than a linearized protein library, search times are decreased and the process is decoupled from any specific search engine. A further benefit of decoupling from the search engine is that protein cross-linking studies may be conducted with readily available informatics tools for which scoring routines already exist within the proteomic community.
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We developed an informatic method to identify tandem mass spectra composed of chemically cross-linked peptides from those of linear peptides and to assign sequence to each of the two unique peptide sequences. For a given set of proteins the key software tool, xComb, combs through all theoretically feasible cross-linked peptides to create a database consisting of a subset of all combinations represented as peptide FASTA files. The xComb library of select theoretical cross-linked peptides may then be used as a database that is examined by a standard proteomic search engine to match tandem mass spectral data sets to identify cross-linked peptides. The database search may be conducted against as many as 50 proteins with a number of common proteomic search engines, e.g. Phenyx, Sequest, OMSSA, Mascot and X!Tandem. By searching against a peptide library of linearized, cross-linked peptides, rather than a linearized protein library, search times are decreased and the process is decoupled from any specific search engine. A further benefit of decoupling from the search engine is that protein cross-linking studies may be conducted with readily available informatics tools for which scoring routines already exist within the proteomic community.
Key concepts: Mascot, Database search engine, Computer science, Search engine, Peptide, Sequence database, Computational biology, Tandem mass spectrometry