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DOI number:

10.1021/acs.jproteome.2c00500

Journal:

Journal of Proteome Research

Key Words:

cross-linking mass spectrometry; database search; peptide identification; protein feedback

Abstract:

Improving the sensitivity of protein−protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/β mass detection scheme and establishes protein−peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

Co-author:

Sheng Lian, Xiaodan Fan, Ning Li, Weichuan Yu

First Author:

Chen Zhou#, Shuaijian Dai#, Yuanqiao Lin#

Indexed by:

Journal paper

Document Type:

Article

Volume:

22

Issue:

1

Page Number:

101-113

ISSN No.:

1535-3893

Translation or Not:

no

Date of Publication:

2022-12-08