RT Journal Article
SR Electronic
T1 Structure-based validation can drastically under-estimate error rate in proteome-wide cross-linking mass spectrometry studies
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 617654
DO 10.1101/617654
A1 Kumar Yugandhar
A1 Ting-Yi Wang
A1 Shayne D. Wierbowski
A1 Elnur Elyar Shayhidin
A1 Haiyuan Yu
YR 2019
UL http://biorxiv.org/content/early/2019/12/25/617654.abstract
AB Recent, rapid advances in cross-linking mass spectrometry (XL-MS) has enabled detection of novel protein-protein interactions and their structural dynamics at the proteome scale. Given the importance and scale of the novel interactions identified in these proteome-wide XL-MS studies, thorough quality assessment is critical. Almost all current XL-MS studies validate cross-links against known 3D structures of representative protein complexes. However, current structure validation approach only includes cross-links where both peptides mapped to the 3D structures. Here we provide theoretical and experimental evidence demonstrating this approach can drastically underestimate error rates for proteome-wide XL-MS datasets. Addressing current shortcomings, we propose and demonstrate a comprehensive set of four metrics, including orthogonal experimental validation to thoroughly assess quality of proteome-wide XL-MS datasets.