Cross‐linked peptide identification: A computational forest of algorithms

Abstract

Chemical cross-linking analyzed by mass spectrometry (XL-MS) has become an important tool in unravelling protein structure, dynamics, and complex formation. Because the analysis of cross-linked proteins with mass spectrometry results in specific computational challenges, many computational tools have been developed to identify cross-linked peptides from mass spectra and subsequently interpret the identified cross-links within their structural context. In this review, we will provide an overview of the different tools that are currently available to tackle the computational part of an XL-MS experiment. First, we give an introduction on the computational challenges encountered when processing data from a cross-linking experiment. We then discuss available tools to identify peptides that are linked by intact or MS-cleavable cross-linkers, and we provide an overview of tools to interpret cross-linked peptides in the context of protein structure. Finally, we give an outlook on data management and dissemination challenges and opportunities for cross-linking experiments.

PyXlinkViewer: a flexible tool for visualisation of protein chemical crosslinking data within the PyMOL molecular graphics system

“…Recent enhancements in XL-MS protocols (6; 27; 26), new crosslinker designs (28), and refined bioinformatics approaches (8), have ensured XL-MS is a key tool in the structural biologist's armory of methods for determination of the structure and dynamics of proteins and their complexes both in vitro and in vivo. Computational modelling methods using XL-MS restraints are being constantly improved (15; 29; 14; 16), but a vital, final step in this pipeline is the comparison of structures/structural models with XL-MS data.…”

“…After manual curation of an appropriate XL-MS dataset using dedicated XL-MS analysis software (8), the data are prepared as a list of crosslinks and dead-ends for use in PyXlinkViewer. This approach enables the user to curate their dataset and filter it based on the score of the detected crosslinks (each data analysis software package uses a different scoring algorithm) prior to data visualisation.…”

“…To visualise dead-end or covalent labelling/footprinting data, only one residue/chain identifier is included in each entry (see example data). There are a number of different file formats generated by the various XL-MS data processing tools (8). However, recently a XL-MS file conversion utility has been created (20), and a standard XL-MS data format proposed.…”

“…These peptides are of relatively low abundance compared to their non-crosslinked counterparts, so much work has focused on developing analytical workflows to enable crosslink detection (e.g. using enrichment protocols (6), incorporating MS-cleavable groups in the spacer arm that yield diagnostic fragment ions (7), and developing specialised informatics tools (8)). The detected crosslinks can be mapped onto protein sequences/networks (e.g.…”

Rapid Mapping of Protein Interactions Using Tag‐Transfer Photocrosslinkers

“…Chemical crosslinking‐mass spectrometry (XL‐MS) is a powerful component of the structural biology toolkit . XL‐MS methods have been enhanced by new data analysis software, cleavable crosslinkers, strategies for crosslink enrichment, footprinting reagents, and structural modelling approaches . However, several challenges remain.…”