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Crosslinking-mass spectrometry (XL-MS) serves to identify interaction sites between proteins. Numerous search engines for crosslink identification exist, but lack of ground truth samples containing known crosslinks has precluded their systematic validation. Here we report on XL-MS data arising from measuring synthetic peptide libraries that provide the unique benefit of knowing which identified crosslinks are true and which are false. The data are analysed with the most frequently used search engines and the results filtered to an estimated false discovery rate of 5%. We find that the actual false crosslink identification rates range from 2.4 to 32%, depending on the analysis strategy employed. Furthermore, the use of MS-cleavable crosslinkers does not reduce the false discovery rate compared to non-cleavable crosslinkers. We anticipate that the datasets acquired during this research will further drive optimisation and development of XL-MS search engines, thereby advancing our understanding of vital biological interactions.

Protein phosphorylation regulates key processes in all organisms. In Gram-positive bacteria, protein arginine phosphorylation plays a central role in protein quality control by regulating transcription factors and marking aberrant proteins for degradation. Here, we report structural, biochemical, and in vivo data of the responsible kinase, McsB, the founding member of an arginine-specific class of protein kinases. McsB differs in structure and mechanism from protein kinases that act on serine, threonine, and tyrosine residues and instead has a catalytic domain related to that of phosphagen kinases (PhKs), metabolic enzymes that phosphorylate small guanidino compounds. In McsB, the PhK-like phosphotransferase domain is structurally adapted to target protein substrates and is accompanied by a novel phosphoarginine (pArg)-binding domain that allosterically controls protein kinase activity. The identification of distinct pArg reader domains in this study points to a remarkably complex signaling system, thus challenging simplistic views of bacterial protein phosphorylation.

In the version of this article initially published online, the authors used incorrectly defined restraints for specifying the distance between residues when using the HADDOCK portal. Following the publication of a Correspondence by the developers of the HADDOCK portal (Nat. Protoc. https://dx.doi.org/10.1038/s41596-018-0017-6, 2018) and a Reply by the authors of the Protocol (Nat. Protoc. https://dx.doi.org/10.1038/s41596-018-0018-5, 2018), the syntax in step 21 has been corrected. In addition, the input files (available as Supplementary Data 5-7) have been replaced.

This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

Fdc1 is a decarboxylase enzyme that requires the novel prenylated FMN cofactor for activity. Here, we use it as an exemplar system to show how native top-down and bottom-up mass spectrometry can measure the structural effect of cofactor binding by a protein. For Fdc1(Ubix), the cofactor confers structural stability to the enzyme. IM-MS shows the holo protein to exist in four closely related conformational families, the populations of which differ in the apo form; the two smaller families are more populated in the presence of the cofactor and depopulated in its absence. These findings, supported by MD simulations, indicate a more open structure for the apo form. HDX-MS reveals that while the dominant structural changes occur proximal to the cofactor-binding site, rearrangements on cofactor binding are evident throughout the protein, predominantly attributable to allosteric conformational tightening, consistent with IM-MS data.