Quantitative Structural Interpretation of Protein Crosslinks

Abstract

Chemical cross-linking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting the physico-chemical interactions between the cross-linker and the protein and of flexibility. Here we present a method, named NRGXL (New Realistic Grid for Cross-Links), which models the flexibility of the cross-linker and the linked side chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the cross-linker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent accessible distance and its efficiency makes it usable for validating 3D models from cross-linking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr.

Evaluation of acquisition modes for semi‐quantitative analysis by targeted and untargeted mass spectrometry

“…Metabolites and peptides are some of the most common analytes subjected to analysis by quantitative MS; however, they are certainly not the only species for which such analysis would be beneficial. One newer area in which quantitative analysis is of interest is in the field of cross‐linking‐mass spectrometry (XL‐MS), where success has been achieved using both isotopic labeling and label‐free approaches for (semi‐) quantitation to date 42–46 . Quantitation in the context of XL‐MS facilitates comparative analysis of multiple samples in parallel, characterizing variation in protein structure and interactions under different conditions.…”

“…One newer area in which quantitative analysis is of interest is in the field of cross‐linking‐mass spectrometry (XL‐MS), where success has been achieved using both isotopic labeling and label‐free approaches for (semi‐) quantitation to date. 42 , 43 , 44 , 45 , 46 Quantitation in the context of XL‐MS facilitates comparative analysis of multiple samples in parallel, characterizing variation in protein structure and interactions under different conditions. It is acknowledged, however, that quantitative XL‐MS is a challenging area of research, due in part to the variation in cross‐linked peptide abundance within a sample, and ion suppression effects that could result from this.…”

Leveraging crosslinking mass spectrometry in structural and cell biology

“…Recently, the Topf group has developed XLM-Tools, a program to score models on a combination of crosslinker SASD and experimental detection of crosslinker-modified linear peptides (''monolinks'') into a single crosslink/monolink combined score (Sinnott et al, 2020). Interestingly, it has been shown that incorporating normal mode analysis or other approaches to generate protein motion in silico increases the precision and accuracy of scoring crosslinks with both SASD and NRGXL, further confirming the need to account for the in-solution nature of the crosslinking-MS measurement (Degiacomi et al, 2017;Filella-Merce et al, 2020).…”

Do Not Waste Time─Ensure Success in Your Cross-Linking Mass Spectrometry Experiments before You Begin

“…As cross-linkers have known spacer lengths, the distance constraints they provide has made XL-MS a valuable resource for structural characterization of proteins and their assemblies, including highly dynamic systems with many interactions. − XL-MS data is frequently used in conjunction with data from other structural techniques, notably X-ray crystallography and cryo-electron microscopy to provide complementary information, , such as additional protein states, filling in structural resolution gaps, and assist in protein identification of unknown densities . Cross-linking data is also used in computational modeling ,− to either improve on existing proteins models or through de novo modeling if a structure from the PDB or a suitable model is not available, with new tools emerging to aid in more realistic protein modeling, taking into consideration protein energy landscapes. − Another major application of XL-MS is identifying protein–protein interactions (PPIs), − especially as the field has quickly moved toward complex systems and in vivo (or in-cell) cross-linking. In vivo cross-linking allows for a global overview of protein interactions without prior assumptions as it preserves potential transient interactions and offers the possibility of detecting novel PPIs that may be lost during purification.…”