Kojak: Efficient analysis of chemically cross-linked protein complexes - Hoopmann, Michael R. (J Proteome Res, 2015)
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 datasets, and was compared with 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 datasets. For new users, it provides a simple analytical resource resulting in more cross-link identifications than other methods.