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Kojak: Efficient Analysis of Chemically Cross-Linked Protein Complexes

2015; American Chemical Society; Volume: 14; Issue: 5 Linguagem: Inglês

10.1021/pr501321h

1535-3907

Michael R. Hoopmann, Alex Zelter, Richard S. Johnson, Michael Riffle, Michael J. MacCoss, Trisha N. Davis, Robert L. Moritz,

Monoclonal and Polyclonal Antibodies Research

Protein chemical cross-linking and mass spectrometry enable the analysis of protein–protein interactions and protein topologies; however, complicated cross-linked peptide spectra require specialized algorithms to identify interacting sites. The Kojak cross-linking software application is a new, efficient approach to identify cross-linked peptides, enabling large-scale analysis of protein–protein interactions by chemical cross-linking techniques. The algorithm integrates spectral processing and scoring schemes adopted from traditional database search algorithms and can identify cross-linked peptides using many different chemical cross-linkers with or without heavy isotope labels. Kojak was used to analyze both novel and existing data sets and was compared to existing cross-linking algorithms. The algorithm provided increased cross-link identifications over existing algorithms and, equally importantly, the results in a fraction of computational time. The Kojak algorithm is open-source, cross-platform, and freely available. This software provides both existing and new cross-linking researchers alike an effective way to derive additional cross-link identifications from new or existing data sets. For new users, it provides a simple analytical resource resulting in more cross-link identifications than other methods.