Structure-based validation can drastically under-estimate error rate in proteome-wide cross-linking mass spectrometry studies

Cross-linking mass spectrometry (XL-MS) is an increasingly popular technique for capturing large-scale interactions and their structural dynamics. Almost all proteome-wide XL-MS studies to date validate their identified cross-links by mapping them onto the available 3D structures of representative complexes such as ribosome and proteasome. Here, we theoretically demonstrate and experimentally confirm that such a structure-based validation approach can drastically under-estimate the underlying error rate. Given the broad use and interest in these XL-MS datasets, the unexpected high number of false positives will severely hinder the development of the field and the utility of these datasets. Thus, it is of utmost importance to bring this problem to the attention of the field.