Enhancing Inter-link Coverage in Cross-Linking Mass Spectrometry through Context-Sensitive Subgrouping and Decoy Fusion

bioRxiv (Cold Spring Harbor Laboratory)(2023)

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摘要
In cross-linking mass spectrometry, sensitivity and specificity in assigning mass spectra to cross-links between different proteins (inter-links) remains challenging. Here, we report on limitations of commonly used concatenated target-decoy searches and propose a target-decoy competition strategy on a fused database as a solution. Further, we capitalize on context-divergent error rates by implementing a novel context-sensitive subgrouping strategy. This approach increases inter-link coverage by ∼ 30 - 75 % across XL-MS datasets, maintains low error rates, and preserves structural accuracy. ### Competing Interest Statement The authors have declared no competing interest.
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关键词
decoy fusion,inter-link,cross-linking,context-sensitive
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