Protein-protein interactions are key to function and regulation of many biological pathways. To facilitate characterization of protein-protein interactions using mass spectrometry, a new data acquisition/analysis pipeline was designed. The goal for this pipeline was to provide a generic strategy for identifying cross-linked peptides from single LC/MS/MS data sets, without using specialized cross-linkers or custom-written software. To achieve this, each peptide in the pair of cross-linked peptides was considered to be "post-translationally" modified with an unknown mass at an unknown amino acid. This allowed use of an open-modification search engine, Popitam, to interpret the tandem mass spectra of cross-linked peptides. False positives were reduced and database selectivity increased by acquiring precursors and fragments at high mass accuracy. Additionally, a high-charge-state-driven data acquisition scheme was utilized to enrich data sets for cross-linked peptides. This open-modification search based pipeline was shown to be useful for characterizing both chemical as well as native cross-links in proteins. The pipeline was validated by characterizing the known interactions in the chemically cross-linked CYP2E1-b5 complex. Utility of this method in identifying native cross-links was demonstrated by mapping disulfide bridges in RcsF, an outer membrane lipoprotein involved in Rcs phosphorelay.