Exhaustive Cross-Linking Search with Protein Feedback
DOI码:10.1021/acs.jproteome.2c00500
发表刊物:Journal of Proteome Research
关键字:cross-linking mass spectrometry; database search; peptide identification; protein feedback
摘要: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.
合写作者:Sheng Lian, Xiaodan Fan, Ning Li, Weichuan Yu
第一作者:Chen Zhou#, Shuaijian Dai#, Yuanqiao Lin#
论文类型:期刊论文
文献类型:Article
卷号:22
期号:1
页面范围:101-113
ISSN号:1535-3893
是否译文:否
发表时间:2022-12-08
