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

ABSTRACT: Thorough quality assessment of novel interactions identified by proteome-wide cross-linking mass spectrometry (XL-MS) studies is critical. Almost all current XL-MS studies have validated cross-links against known three-dimensional structures of representative protein complexes. Here, we provide theoretical and experimental evidence demonstrating that this approach can drastically underestimate error rates for proteome-wide XL-MS datasets, and propose a comprehensive set of four data-quality metrics to address this issue.

SUBMITTER: Yugandhar K

PROVIDER: S-EPMC7534832 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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

Yugandhar Kumar K Wang Ting-Yi TY Wierbowski Shayne D SD Shayhidin Elnur Elyar EE Yu Haiyuan H

Nature methods 20200929 10

Thorough quality assessment of novel interactions identified by proteome-wide cross-linking mass spectrometry (XL-MS) studies is critical. Almost all current XL-MS studies have validated cross-links against known three-dimensional structures of representative protein complexes. Here, we provide theoretical and experimental evidence demonstrating that this approach can drastically underestimate error rates for proteome-wide XL-MS datasets, and propose a comprehensive set of four data-quality metr ...[more]

PMID: 32994567

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